Configuration Parsing Warning:Config file tokenizer_config.json cannot be fetched (too big)
Configuration Parsing Warning:Config file adapter_config.json cannot be fetched (too big)
YAML Metadata Warning:The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Model Card for Model ID
This is a kindergarten-teacher-style text-to-text generation model fined tuned on Qwen1.5-1.8B. It gives answers to any input question like a gentle and warm kindergarten teacher.
Model Details
Model Description
- Developed by: Miao025
- Model type: Causal Language Model (decoder-only)
- Model size: 1.8B params
- Language(s) (NLP): English
- License: apache-2.0
- Finetuned from model [optional]: Qwen/Qwen1.5-1.8B
- Demo: A fine-tuned AI KinderChatbot based on this sft model
Useage
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Load tokenizer and fine-tuned model (Note that you can also download the models and load with local path.)
tokenizer_sft = AutoTokenizer.from_pretrained("Miao025/Qwen-KinderChatbot-LoRA")
sft_model = AutoModelForCausalLM.from_pretrained("Miao025/Qwen-KinderChatbot-LoRA").to("cuda") # Recommend to use gpu as this is a large model
# Prepare prompt
prompt = "Why do we need to brush our teeth?"
inputs = tokenizer_sft(prompt, return_tensors="pt", truncation=True).to("cuda")
# Generate a response
output = sft_model.generate(**inputs)
# Decode the result
response = tokenizer_sft.decode(output[0], skip_special_tokens=True)
Training Data
[Training Dataset Card](to be add) Training process can be found on Github.
Contact
For any questions, please contact the author yinmiao025@gmail.com
- Downloads last month
- 9
Model tree for Miao025/Qwen-KinderChatbot-LoRA
Base model
Qwen/Qwen1.5-1.8B