repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/colossal_eval/evaluate/__init__.py | applications/ColossalEval/colossal_eval/evaluate/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/metrics.py | applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/metrics.py | # Code adapted from https://github.com/THUDM/LongBench/blob/main/metrics.py
# Code adapted from https://github.com/hendrycks/math/blob/main/modeling/math_equivalence.py
# Code adapted from https://github.com/ruixiangcui/AGIEval/blob/main/src/evaluation.py
# https://github.com/SkyworkAI/Skywork/blob/main/eval/eval_gsm8k... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/gpt_judge.py | applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/gpt_judge.py | # Code adapted from https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge
import ast
import concurrent.futures
import copy
import json
import os
import re
import time
from typing import Any, Dict, List
import numpy as np
import openai
import tqdm
MODEL = "gpt-4"
API_MAX_RETRY = 16
API_RETRY_SLEEP = 10
API... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/__init__.py | applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/__init__.py | from .dataset_evaluator import DatasetEvaluator
__all__ = ["DatasetEvaluator"]
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/dataset_evaluator.py | applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/dataset_evaluator.py | import os
from typing import Dict, List, Union
import colossal_eval.evaluate.dataset_evaluator.metrics as metric_helper
import numpy as np
import tqdm
from colossal_eval.utils import jdump
import colossal_eval.evaluate.dataset_evaluator.gpt_judge as gpt_helper # noqa
LabelBasedMetrics = ["first_token_accuracy", "ma... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/examples/dataset_evaluation/inference.py | applications/ColossalEval/examples/dataset_evaluation/inference.py | import argparse
import copy
import os
from typing import Dict, List
import torch.distributed as dist
from colossal_eval import dataset, models, utils
from colossal_eval.dataset.base import DistributedDataset
from torch.utils.data import DataLoader, DistributedSampler
import colossalai
from colossalai.accelerator impo... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/examples/dataset_evaluation/eval_dataset.py | applications/ColossalEval/examples/dataset_evaluation/eval_dataset.py | import argparse
import os
import tabulate
from colossal_eval.evaluate.dataset_evaluator import DatasetEvaluator
from colossal_eval.utils import jdump, jload
def main(args):
config = jload(args.config)
evaluation_results = {dataset["name"]: {} for dataset in config["dataset"]}
evaluation_results_table = ... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/examples/gpt_evaluation/inference.py | applications/ColossalEval/examples/gpt_evaluation/inference.py | import argparse
import copy
import os
from typing import Dict, List
import torch
import torch.distributed as dist
from colossal_eval import dataset, models, utils
import colossalai
from colossalai.cluster import ProcessGroupMesh
from colossalai.logging import get_dist_logger
from colossalai.shardformer import ShardCo... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalEval/examples/gpt_evaluation/eval.py | applications/ColossalEval/examples/gpt_evaluation/eval.py | import argparse
import os
import openai
from colossal_eval.evaluate.evaluator import Evaluator
from colossal_eval.utils import jload
def main(args):
assert len(args.answer_file_list) == len(
args.model_name_list
), "The number of answer files and model names should be equal!"
# load config
c... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/setup.py | applications/ColossalQA/setup.py | from setuptools import find_packages, setup
def fetch_requirements(path):
with open(path, "r") as fd:
return [r.strip() for r in fd.readlines()]
def fetch_readme():
with open("README.md", encoding="utf-8") as f:
return f.read()
def fetch_version():
with open("version.txt", "r") as f:
... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/mylogging.py | applications/ColossalQA/colossalqa/mylogging.py | """
Class for logging with extra control for debugging
"""
import logging
class ColossalQALogger:
"""This is a distributed event logger class essentially based on :class:`logging`.
Args:
name (str): The name of the logger.
Note:
Logging types: ``info``, ``warning``, ``debug`` and ``erro... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/retrieval_conversation_en.py | applications/ColossalQA/colossalqa/retrieval_conversation_en.py | """
Script for Chinese retrieval based conversation system backed by ChatGLM
"""
from typing import Tuple
from colossalqa.chain.retrieval_qa.base import RetrievalQA
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.memory import ConversationBufferWithSummary
from colossalqa.mylogging import ge... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/memory.py | applications/ColossalQA/colossalqa/memory.py | """
Implement a memory class for storing conversation history
Support long term and short term memory
"""
from typing import Any, Dict, List
from colossalqa.chain.memory.summary import ConversationSummaryMemory
from colossalqa.chain.retrieval_qa.load_chain import load_qa_chain
from langchain.chains.combine_documents.... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/retrieval_conversation_zh.py | applications/ColossalQA/colossalqa/retrieval_conversation_zh.py | """
Script for Chinese retrieval based conversation system backed by ChatGLM
"""
from typing import Tuple
from colossalqa.chain.retrieval_qa.base import RetrievalQA
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.memory import ConversationBufferWithSummary
from colossalqa.mylogging import ge... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/utils.py | applications/ColossalQA/colossalqa/utils.py | import re
from typing import Union
from colossalqa.mylogging import get_logger
from sqlalchemy import Engine, MetaData, create_engine
from sqlalchemy.exc import SQLAlchemyError
from sqlalchemy.ext.declarative import declarative_base
logger = get_logger()
def drop_table(engine: Engine) -> None:
"""
Drop all ... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/__init__.py | applications/ColossalQA/colossalqa/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/retriever.py | applications/ColossalQA/colossalqa/retriever.py | """
Code for custom retriver with incremental update
"""
import copy
import hashlib
import os
from collections import defaultdict
from typing import Any, Callable, Dict, List
from colossalqa.mylogging import get_logger
from langchain.callbacks.manager import CallbackManagerForRetrieverRun
from langchain.embeddings.ba... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/retrieval_conversation_universal.py | applications/ColossalQA/colossalqa/retrieval_conversation_universal.py | """
Multilingual retrieval based conversation system
"""
from typing import List
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.mylogging import get_logger
from colossalqa.retrieval_conversation_en import EnglishRetrievalConversation
from colossalqa.retrieval_conversation_zh import ... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/chain/__init__.py | applications/ColossalQA/colossalqa/chain/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/chain/memory/summary.py | applications/ColossalQA/colossalqa/chain/memory/summary.py | """
Custom SummarizerMixin base class and ConversationSummaryMemory class
Modified from Original Source
This code is based on LangChain Ai's langchain, which can be found at
https://github.com/langchain-ai/langchain
The original code is licensed under the MIT license.
"""
from __future__ import annotations
from typ... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/chain/memory/__init__.py | applications/ColossalQA/colossalqa/chain/memory/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/chain/retrieval_qa/stuff.py | applications/ColossalQA/colossalqa/chain/retrieval_qa/stuff.py | """
Chain that combines documents by stuffing into context
Modified from Original Source
This code is based on LangChain Ai's langchain, which can be found at
https://github.com/langchain-ai/langchain
The original code is licensed under the MIT license.
"""
import copy
from typing import Any, List
from langchain.ch... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/chain/retrieval_qa/__init__.py | applications/ColossalQA/colossalqa/chain/retrieval_qa/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/chain/retrieval_qa/base.py | applications/ColossalQA/colossalqa/chain/retrieval_qa/base.py | """
Chain for question-answering against a vector database.
Modified from Original Source
This code is based on LangChain Ai's langchain, which can be found at
https://github.com/langchain-ai/langchain
The original code is licensed under the MIT license.
"""
from __future__ import annotations
import copy
import ins... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/chain/retrieval_qa/load_chain.py | applications/ColossalQA/colossalqa/chain/retrieval_qa/load_chain.py | """
Load question answering chains.
For now, only the stuffed chain is modified
Modified from Original Source
This code is based on LangChain Ai's langchain, which can be found at
https://github.com/langchain-ai/langchain
The original code is licensed under the MIT license.
"""
import copy
from typing import Any, Ma... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/prompt/prompt.py | applications/ColossalQA/colossalqa/prompt/prompt.py | """
All custom prompt templates are defined here.
"""
from langchain.prompts.prompt import PromptTemplate
# Below are Chinese retrieval qa prompts
_CUSTOM_SUMMARIZER_TEMPLATE_ZH = """请递进式地总结所提供的当前对话，将当前对话的摘要内容添加到先前已有的摘要上，返回一个融合了当前对话的新的摘要。
例1:
已有的摘要:
人类问Assistant对人工智能的看法。人工智能认为人工智能是一种善的力量。
新的对话内容:
人类: 为什么你认为人工智能是一种... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/text_splitter/utils.py | applications/ColossalQA/colossalqa/text_splitter/utils.py | import re
def remove_format(text: str) -> str:
# if the accout of \t, \r, \v, \f is less than 3, replace \t, \r, \v, \f with space
if len(re.findall(r"\s", text.replace(" ", ""))) > 3:
# in case this is a line of a table
return text
return re.sub(r"\s", " ", text)
# remove newlines
def g... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/text_splitter/chinese_text_splitter.py | applications/ColossalQA/colossalqa/text_splitter/chinese_text_splitter.py | """
Code for Chinese text splitter
"""
from typing import Any, List, Optional
from colossalqa.text_splitter.utils import get_cleaned_paragraph
from langchain.text_splitter import RecursiveCharacterTextSplitter
class ChineseTextSplitter(RecursiveCharacterTextSplitter):
def __init__(self, separators: Optional[Lis... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/text_splitter/__init__.py | applications/ColossalQA/colossalqa/text_splitter/__init__.py | from .chinese_text_splitter import ChineseTextSplitter
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/local/llm.py | applications/ColossalQA/colossalqa/local/llm.py | """
API and LLM warpper class for running LLMs locally
Usage:
import os
model_path = os.environ.get("ZH_MODEL_PATH")
model_name = "chatglm2"
colossal_api = ColossalAPI(model_name, model_path)
llm = ColossalLLM(n=1, api=colossal_api)
TEST_PROMPT_CHATGLM="续写文章：惊蛰一过，春寒加剧。先是料料峭峭，继而雨季开始，"
logger.info(llm(TEST_PROMPT_CHATG... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/local/pangu_llm.py | applications/ColossalQA/colossalqa/local/pangu_llm.py | """
LLM wrapper for Pangu
Usage:
# URL: “盘古大模型套件管理”->点击“服务管理”->“模型列表”->点击想要使用的模型的“复制路径”
# USERNAME: 华为云控制台：“我的凭证”->“API凭证”下的“IAM用户名”，也就是你登录IAM账户的名字
# PASSWORD: IAM用户的密码
# DOMAIN_NAME: 华为云控制台：“我的凭证”->“API凭证”下的“用户名”，也就是公司管理IAM账户的总账户名
os.environ["URL"] = ""
os.environ["URLNAME"] = ""
os.environ["PASSWORD"] = ""
os.envi... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/local/utils.py | applications/ColossalQA/colossalqa/local/utils.py | """
Generation utilities
"""
import json
from typing import List
import requests
def post_http_request(
prompt: str, api_url: str, n: int = 1, max_tokens: int = 100, temperature: float = 0.0, stream: bool = False
) -> requests.Response:
headers = {"User-Agent": "Test Client"}
pload = {
"prompt":... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/local/colossalcloud_llm.py | applications/ColossalQA/colossalqa/local/colossalcloud_llm.py | """
LLM wrapper for LLMs running on ColossalCloud Platform
Usage:
os.environ['URL'] = ""
os.environ['HOST'] = ""
gen_config = {
'max_new_tokens': 100,
# 'top_k': 2,
'top_p': 0.9,
'temperature': 0.5,
'repetition_penalty': 2,
}
llm = ColossalCloudLLM(n=1)
llm.set_auth_confi... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/local/__init__.py | applications/ColossalQA/colossalqa/local/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/data_loader/document_loader.py | applications/ColossalQA/colossalqa/data_loader/document_loader.py | """
Class for loading document type data
"""
import glob
from typing import List
from colossalqa.mylogging import get_logger
from langchain.document_loaders import (
JSONLoader,
PyPDFLoader,
TextLoader,
UnstructuredHTMLLoader,
UnstructuredMarkdownLoader,
)
from langchain.document_loaders.csv_loade... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/data_loader/table_dataloader.py | applications/ColossalQA/colossalqa/data_loader/table_dataloader.py | """
Class for loading table type data. please refer to Pandas-Input/Output for file format details.
"""
import glob
import os
import pandas as pd
from colossalqa.mylogging import get_logger
from colossalqa.utils import drop_table
from sqlalchemy import create_engine
logger = get_logger()
SUPPORTED_DATA_FORMAT = [".... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/colossalqa/data_loader/__init__.py | applications/ColossalQA/colossalqa/data_loader/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/tests/test_retrieval_qa.py | applications/ColossalQA/tests/test_retrieval_qa.py | import os
from colossalqa.retrieval_conversation_universal import UniversalRetrievalConversation
def test_en_retrievalQA():
data_path_en = os.environ.get("TEST_DATA_PATH_EN")
data_path_zh = os.environ.get("TEST_DATA_PATH_ZH")
en_model_path = os.environ.get("EN_MODEL_PATH")
zh_model_path = os.environ.... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/tests/test_text_splitter.py | applications/ColossalQA/tests/test_text_splitter.py | from colossalqa.text_splitter.chinese_text_splitter import ChineseTextSplitter
def test_text_splitter():
# unit test
spliter = ChineseTextSplitter(chunk_size=30, chunk_overlap=0)
out = spliter.split_text(
"移动端语音唤醒模型，检测关键词为“小云小云”。模型主体为4层FSMN结构，使用CTC训练准则，参数量750K，适用于移动端设备运行。模型输入为Fbank特征，输出为基于char建模的中... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/tests/test_memory.py | applications/ColossalQA/tests/test_memory.py | import os
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.memory import ConversationBufferWithSummary
from colossalqa.prompt.prompt import PROMPT_RETRIEVAL_QA_ZH
from colossalqa.retriever import CustomRetriever
from langchain.e... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/tests/__init__.py | applications/ColossalQA/tests/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/tests/test_document_loader.py | applications/ColossalQA/tests/test_document_loader.py | import os
from colossalqa.data_loader.document_loader import DocumentLoader
def test_add_document():
PATH = os.environ.get("TEST_DOCUMENT_LOADER_DATA_PATH")
files = [[PATH, "all data"]]
document_loader = DocumentLoader(files)
documents = document_loader.all_data
all_files = []
for doc in docu... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/retrieval_conversation_en.py | applications/ColossalQA/examples/retrieval_conversation_en.py | """
Script for English retrieval based conversation system backed by LLaMa2
"""
import argparse
import os
from colossalqa.chain.retrieval_qa.base import RetrievalQA
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.memory import... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/retrieval_intent_classification_zh_customer_service.py | applications/ColossalQA/examples/retrieval_intent_classification_zh_customer_service.py | """
Script for English retrieval based conversation system backed by LLaMa2
"""
import argparse
import os
from colossalqa.chain.retrieval_qa.base import RetrievalQA
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.prompt.prompt... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/retrieval_conversation_en_customer_service.py | applications/ColossalQA/examples/retrieval_conversation_en_customer_service.py | """
Script for English retrieval based conversation system backed by LLaMa2
"""
import argparse
import json
import os
from colossalqa.chain.retrieval_qa.base import RetrievalQA
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.m... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/retrieval_conversation_chatgpt.py | applications/ColossalQA/examples/retrieval_conversation_chatgpt.py | """
Multilingual retrieval based conversation system backed by ChatGPT
"""
import argparse
import os
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.memory import ConversationBufferWithSummary
from colossalqa.retriever import CustomRetriever
from langchain import LLMChain
from langch... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/retrieval_conversation_zh.py | applications/ColossalQA/examples/retrieval_conversation_zh.py | """
Script for Chinese retrieval based conversation system backed by ChatGLM
"""
import argparse
import os
from colossalqa.chain.retrieval_qa.base import RetrievalQA
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.memory impor... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/conversation_agent_chatgpt.py | applications/ColossalQA/examples/conversation_agent_chatgpt.py | """
Script for the multilingual conversation based experimental AI agent
We used ChatGPT as the language model
You need openai api key to run this script
"""
import argparse
import os
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.data_loader.table_dataloader import TableLoader
from... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/retrieval_conversation_universal.py | applications/ColossalQA/examples/retrieval_conversation_universal.py | import argparse
from colossalqa.retrieval_conversation_universal import UniversalRetrievalConversation
if __name__ == "__main__":
# Parse arguments
parser = argparse.ArgumentParser()
parser.add_argument("--en_model_path", type=str, default=None)
parser.add_argument("--zh_model_path", type=str, default... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/webui_demo/RAG_ChatBot.py | applications/ColossalQA/examples/webui_demo/RAG_ChatBot.py | import os
from typing import Dict, Tuple
from colossalqa.chain.retrieval_qa.base import RetrievalQA
from colossalqa.data_loader.document_loader import DocumentLoader
from colossalqa.memory import ConversationBufferWithSummary
from colossalqa.mylogging import get_logger
from colossalqa.prompt.prompt import ZH_RETRIEVAL... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/webui_demo/webui.py | applications/ColossalQA/examples/webui_demo/webui.py | import argparse
import json
import os
import gradio as gr
import requests
from utils import DocAction
def parseArgs():
parser = argparse.ArgumentParser()
parser.add_argument("--http_host", default="0.0.0.0")
parser.add_argument("--http_port", type=int, default=13666)
return parser.parse_args()
def ... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/webui_demo/utils.py | applications/ColossalQA/examples/webui_demo/utils.py | from enum import Enum
class DocAction(str, Enum):
ADD = "add"
CLEAR = "clear"
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/webui_demo/config.py | applications/ColossalQA/examples/webui_demo/config.py | from colossalqa.prompt.prompt import PROMPT_DISAMBIGUATE_ZH, PROMPT_RETRIEVAL_QA_ZH, SUMMARY_PROMPT_ZH
from colossalqa.text_splitter import ChineseTextSplitter
ALL_CONFIG = {
"embed": {
"embed_name": "m3e", # embedding model name
"embed_model_name_or_path": "moka-ai/m3e-base", # path to embedding... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalQA/examples/webui_demo/server.py | applications/ColossalQA/examples/webui_demo/server.py | import argparse
from typing import List, Union
import config
import uvicorn
from colossalqa.local.llm import ColossalAPI, ColossalLLM
from colossalqa.mylogging import get_logger
from fastapi import FastAPI, Request
from pydantic import BaseModel
from RAG_ChatBot import RAG_ChatBot
from utils import DocAction
logger =... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalMoE/train.py | applications/ColossalMoE/train.py | import argparse
import torch
import torch.distributed as dist
from torch.utils.data import Dataset
from tqdm import tqdm
from transformers import AutoTokenizer
from transformers.models.mixtral import MixtralForCausalLM
from utils import load_checkpoint, move_to_cuda, save_checkpoint
import colossalai
from colossalai.... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalMoE/infer.py | applications/ColossalMoE/infer.py | import argparse
import torch
import torch.distributed as dist
from transformers import AutoTokenizer
from transformers.models.mixtral import MixtralConfig, MixtralForCausalLM
import colossalai
from colossalai.booster import Booster
from colossalai.booster.plugin.moe_hybrid_parallel_plugin import MoeHybridParallelPlug... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalMoE/setup.py | applications/ColossalMoE/setup.py | from setuptools import find_packages, setup
def fetch_requirements(path):
with open(path, "r") as fd:
return [r.strip() for r in fd.readlines()]
def fetch_readme():
with open("README.md", encoding="utf-8") as f:
return f.read()
def fetch_version():
with open("version.txt", "r") as f:
... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalMoE/utils.py | applications/ColossalMoE/utils.py | import json
import os
from typing import Any, Dict, Tuple, Union
import torch
from torch.optim.lr_scheduler import _LRScheduler
from torch.optim.optimizer import Optimizer
from colossalai.booster import Booster
from colossalai.cluster import DistCoordinator
def move_to_cuda(batch, device):
return {k: v.to(devic... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalMoE/tests/__init__.py | applications/ColossalMoE/tests/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/train.py | applications/Colossal-LLaMA/train.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Continual Pre-training/Supervised fine-tuning of Colossal-LLaMA-2 developed by Colossal-AI Team
"""
import argparse
import json
import os
import resource
from contextlib import nullcontext
import torch
from colossal_llama.dataset.dummy_dataset import RandomDataset
fr... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/setup.py | applications/Colossal-LLaMA/setup.py | from setuptools import find_packages, setup
def fetch_requirements(path):
with open(path, "r") as fd:
return [r.strip() for r in fd.readlines()]
def fetch_readme():
with open("README.md", encoding="utf-8") as f:
return f.read()
def fetch_version():
with open("version.txt", "r") as f:
... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/dataset/prepare_sft_dataset.py | applications/Colossal-LLaMA/dataset/prepare_sft_dataset.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Prepare sft dataset for fine-tuning
"""
import argparse
import json
import math
import os
from multiprocessing import cpu_count
from colossal_llama.dataset.conversation import LLaMA2_Conv, LLaMA3_Conv
from colossal_llama.dataset.spliced_and_tokenized_dataset import s... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/dataset/prepare_pretrain_dataset.py | applications/Colossal-LLaMA/dataset/prepare_pretrain_dataset.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Prepare dataset for continual pre-training
"""
import argparse
import json
import math
import os
import time
from multiprocessing import cpu_count
from colossal_llama.dataset.spliced_and_tokenized_dataset import (
ClosedToConstantLengthSplicedDataset,
supervi... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/__init__.py | applications/Colossal-LLaMA/colossal_llama/__init__.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/model/init_model.py | applications/Colossal-LLaMA/colossal_llama/model/init_model.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Initialize new model with updated tokenizer by calculating the mean values from original model
"""
import argparse
import numpy as np
import torch
from transformers import LlamaForCausalLM, LlamaTokenizer
from colossalai.logging import get_dist_logger
logger = get_... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/tokenizer/init_tokenizer.py | applications/Colossal-LLaMA/colossal_llama/tokenizer/init_tokenizer.py | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
"""
Initialize new tokenizer for continual pre-training
"""
import argparse
import json
import os
from typing import List, Union
from sentencepiece import sentencepiece_model_pb2 as sp_pb2_model
from transformers.models.llama.tokenization_llama import LlamaTokenizer
f... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/utils/froze.py | applications/Colossal-LLaMA/colossal_llama/utils/froze.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
from transformers.models.llama import LlamaForCausalLM
def freeze_non_embeds_parameters(model: LlamaForCausalLM) -> None:
"""Freeze all parameters except embeddings."""
for name, params in model.named_parameters():
if "embed_tokens" not in name and "lm_h... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/utils/stream_chat_patch.py | applications/Colossal-LLaMA/colossal_llama/utils/stream_chat_patch.py | from copy import deepcopy
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
from torch import nn
from transformers import PreTrainedTokenizer
from transformers.generation.utils import GenerationConfig, LogitsProcessorList, StoppingCriteriaList
from transformers.utils import logging
logger = l... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/utils/utils.py | applications/Colossal-LLaMA/colossal_llama/utils/utils.py | """
Utils for Colossal-LLaMA
"""
import torch
import torch.distributed as dist
from colossalai.booster import Plugin
def all_reduce_mean(tensor: torch.Tensor, plugin: Plugin = None) -> torch.Tensor:
if plugin is not None:
dist.all_reduce(tensor=tensor, op=dist.ReduceOp.SUM, group=plugin.dp_group)
... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/utils/ckpt_io.py | applications/Colossal-LLaMA/colossal_llama/utils/ckpt_io.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Helper functions for IO
"""
import json
import os
from typing import Any, Dict, Tuple, Union
import torch
from torch.optim.lr_scheduler import _LRScheduler
from torch.optim.optimizer import Optimizer
from colossalai.booster import Booster
from colossalai.cluster im... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/utils/__init__.py | applications/Colossal-LLaMA/colossal_llama/utils/__init__.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/utils/neftune_patch.py | applications/Colossal-LLaMA/colossal_llama/utils/neftune_patch.py | # Copyright 2023 The Hugging Face team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/dataset/dummy_dataset.py | applications/Colossal-LLaMA/colossal_llama/dataset/dummy_dataset.py | import torch
from torch.utils.data import Dataset
from colossalai.accelerator import get_accelerator
class RandomDataset(Dataset):
def __init__(self, num_samples: int = 1000, max_length: int = 2048, vocab_size: int = 32000):
self.num_samples = num_samples
self.max_length = max_length
self... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/dataset/loader.py | applications/Colossal-LLaMA/colossal_llama/dataset/loader.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
from dataclasses import dataclass
from typing import Dict, Iterator, List, Optional, Sequence, Union
import torch
import torch.nn.functional as F
from datasets import Dataset as HFDataset
from datasets import dataset_dict, load_from_disk
from torch.utils.data i... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/dataset/conversation.py | applications/Colossal-LLaMA/colossal_llama/dataset/conversation.py | # Copyright 2023 lm-sys@FastChat
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/dataset/__init__.py | applications/Colossal-LLaMA/colossal_llama/dataset/__init__.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/colossal_llama/dataset/spliced_and_tokenized_dataset.py | applications/Colossal-LLaMA/colossal_llama/dataset/spliced_and_tokenized_dataset.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Splicing multiple pre-tokenized sequence data points
"""
import bisect
import random
import warnings
from copy import deepcopy
from typing import Any, Callable, Dict, Iterable, List, Tuple, Union
from datasets import dataset_dict
from torch.utils.data import ConcatDa... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/inference/stream_chat_example.py | applications/Colossal-LLaMA/inference/stream_chat_example.py | import argparse
from colossal_llama.utils.stream_chat_patch import streaming_chat
from transformers import AutoModelForCausalLM, AutoTokenizer
SYSTEM = "A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions."
def m... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/Colossal-LLaMA/inference/inference_example.py | applications/Colossal-LLaMA/inference/inference_example.py | import argparse
import torch
from colossal_llama.dataset.conversation import default_conversation
from transformers import AutoModelForCausalLM, AutoTokenizer
from colossalai.logging import get_dist_logger
logger = get_dist_logger()
def load_model(model_path, device="cuda", **kwargs):
logger.info("Please check... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/setup.py | applications/ColossalChat/setup.py | from setuptools import find_packages, setup
def fetch_requirements(path):
with open(path, "r") as fd:
return [r.strip() for r in fd.readlines()]
def fetch_readme():
with open("README.md", encoding="utf-8") as f:
return f.read()
def fetch_version():
with open("version.txt", "r") as f:
... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/start_code_verifier.py | applications/ColossalChat/start_code_verifier.py | from typing import List, Optional
from coati.distributed.reward.code_reward.utils import check_correctness # Assuming utils.py is in the same directory
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
app = FastAPI()
class CheckCorrectnessRequest(BaseModel):
in_outs: Optional[dict]
... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/rl_example.py | applications/ColossalChat/rl_example.py | import argparse
import json
import os
import ray
import torch
from coati.distributed.launch import launch_distributed
DEFAUT_SYSTEM_PROMPT = {
"think_answer_tags": "You are a helpful assistant. The assistant first thinks about the reasoning process in the mind and then provides the user with the answer. The reaso... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/visualization.py | applications/ColossalChat/visualization.py | # Re-import required libraries due to kernel reset
import argparse
from collections import defaultdict
import matplotlib.cm as cm
import matplotlib.pyplot as plt
# Argument parser for command line arguments
parser = argparse.ArgumentParser(description="Process profiling logs and generate a timeline plot.")
parser.add... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/rl_example_zero_bubble.py | applications/ColossalChat/rl_example_zero_bubble.py | import argparse
import json
import os
import ray
import torch
from coati.distributed.launch_zero_bubble import launch_distributed
DEFAUT_SYSTEM_PROMPT = {
"think_answer_tags": "You are a helpful assistant. The assistant first thinks about the reasoning process in the mind and then provides the user with the answe... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/__init__.py | applications/ColossalChat/coati/__init__.py | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false | |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/quant/utils.py | applications/ColossalChat/coati/quant/utils.py | from contextlib import contextmanager
import torch
def _noop(*args, **kwargs):
pass
@contextmanager
def low_resource_init():
"""This context manager disables weight initialization and sets the default float dtype to half."""
old_kaiming_uniform_ = torch.nn.init.kaiming_uniform_
old_uniform_ = torch... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/quant/__init__.py | applications/ColossalChat/coati/quant/__init__.py | from .llama_gptq import load_quant as llama_load_quant
from .utils import low_resource_init
__all__ = [
"llama_load_quant",
"low_resource_init",
]
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/quant/llama_gptq/quant.py | applications/ColossalChat/coati/quant/llama_gptq/quant.py | # copied from https://github.com/qwopqwop200/GPTQ-for-LLaMa/blob/past/quant.py
import math
import numpy as np
import torch
import torch.nn as nn
def quantize(x, scale, zero, maxq):
q = torch.clamp(torch.round(x / scale) + zero, 0, maxq)
return scale * (q - zero)
class Quantizer(nn.Module):
def __init_... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/quant/llama_gptq/loader.py | applications/ColossalChat/coati/quant/llama_gptq/loader.py | import torch
import torch.nn as nn
from .model_utils import find_layers
from .quant import make_quant
def load_quant(model: nn.Module, checkpoint: str, wbits: int, groupsize: int):
model = model.eval()
layers = find_layers(model)
# ignore lm head
layers = find_layers(model)
for name in ["lm_head... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/quant/llama_gptq/model_utils.py | applications/ColossalChat/coati/quant/llama_gptq/model_utils.py | # copied from https://github.com/qwopqwop200/GPTQ-for-LLaMa/blob/past/modelutils.py
import torch.nn as nn
def find_layers(module, layers=[nn.Conv2d, nn.Linear], name=""):
if type(module) in layers:
return {name: module}
res = {}
for name1, child in module.named_children():
res.update(find... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/quant/llama_gptq/__init__.py | applications/ColossalChat/coati/quant/llama_gptq/__init__.py | from .loader import load_quant
__all__ = [
"load_quant",
]
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/experience_buffer/naive.py | applications/ColossalChat/coati/experience_buffer/naive.py | import random
from typing import List
import torch
from coati.experience_maker.base import Experience
from colossalai.logging import get_dist_logger
from .base import ExperienceBuffer
from .utils import BufferItem, make_experience_batch, split_experience_batch
logger = get_dist_logger()
class NaiveExperienceBuffe... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/experience_buffer/utils.py | applications/ColossalChat/coati/experience_buffer/utils.py | from dataclasses import dataclass
from typing import List, Optional
import torch
import torch.nn.functional as F
from coati.experience_maker.base import Experience
@dataclass
class BufferItem:
"""BufferItem is an item of experience data.
Shapes of each tensor:
sequences: (S)
action_log_probs: (A)
... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/experience_buffer/__init__.py | applications/ColossalChat/coati/experience_buffer/__init__.py | from .base import ExperienceBuffer
from .naive import NaiveExperienceBuffer
__all__ = ["ExperienceBuffer", "NaiveExperienceBuffer"]
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/experience_buffer/base.py | applications/ColossalChat/coati/experience_buffer/base.py | from abc import ABC, abstractmethod
from typing import Any
from coati.experience_maker.base import Experience
class ExperienceBuffer(ABC):
"""Experience buffer base class. It stores experience.
Args:
sample_batch_size (int): Batch size when sampling.
limit (int, optional): Limit of number of... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/experience_maker/naive.py | applications/ColossalChat/coati/experience_maker/naive.py | """
experience maker.
"""
from typing import Any
import torch
import torch.nn.functional as F
from coati.dataset.utils import find_first_occurrence_subsequence
from coati.models import Critic, RewardModel
from coati.models.generation import generate
from coati.models.utils import calc_action_log_probs, compute_reward... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/experience_maker/__init__.py | applications/ColossalChat/coati/experience_maker/__init__.py | from .base import Experience, ExperienceMaker
from .naive import NaiveExperienceMaker
__all__ = ["Experience", "ExperienceMaker", "NaiveExperienceMaker"]
| python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/experience_maker/base.py | applications/ColossalChat/coati/experience_maker/base.py | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Optional
import torch
from coati.models import Critic, RewardModel
from transformers import PreTrainedModel
@dataclass
class Experience:
"""Experience is a batch of data.
These data should have the sequence length and nu... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/models/reward_model.py | applications/ColossalChat/coati/models/reward_model.py | """
reward model
"""
from typing import Optional
import torch
import torch.nn as nn
from coati.models import BaseModel
from transformers import PretrainedConfig
class RewardModel(BaseModel):
"""
Reward model class.
Args:
pretrained str: huggingface or local model path
config: Pretrained... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
hpcaitech/ColossalAI | https://github.com/hpcaitech/ColossalAI/blob/b1915d2889543949eb5b610241f1515c73df5059/applications/ColossalChat/coati/models/lora.py | applications/ColossalChat/coati/models/lora.py | """
LORA utils
"""
import dataclasses
import math
import warnings
from typing import List, Optional, Union
import loralib as lora
import torch
import torch.distributed as dist
import torch.nn as nn
import torch.nn.functional as F
from colossalai.logging import get_dist_logger
logger = get_dist_logger()
@dataclass... | python | Apache-2.0 | b1915d2889543949eb5b610241f1515c73df5059 | 2026-01-04T14:40:19.002665Z | false |
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