Text Generation
Transformers
Safetensors
Korean
English
qwen3_5
image-text-to-text
darwin
korean
reasoning
multimodal
qwen3.5
evolutionary-merge
vidraft
conversational
Instructions to use FINAL-Bench/Darwin-28B-KR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FINAL-Bench/Darwin-28B-KR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FINAL-Bench/Darwin-28B-KR") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("FINAL-Bench/Darwin-28B-KR") model = AutoModelForImageTextToText.from_pretrained("FINAL-Bench/Darwin-28B-KR") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use FINAL-Bench/Darwin-28B-KR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FINAL-Bench/Darwin-28B-KR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FINAL-Bench/Darwin-28B-KR", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/FINAL-Bench/Darwin-28B-KR
- SGLang
How to use FINAL-Bench/Darwin-28B-KR with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "FINAL-Bench/Darwin-28B-KR" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FINAL-Bench/Darwin-28B-KR", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "FINAL-Bench/Darwin-28B-KR" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FINAL-Bench/Darwin-28B-KR", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use FINAL-Bench/Darwin-28B-KR with Docker Model Runner:
docker model run hf.co/FINAL-Bench/Darwin-28B-KR
Update: Darwin-28B-KR v2 - 비드래프트 identity tuning + LoRA(r=16, embed/lm_head) applied
Browse files- README.md +104 -44
- chat_template.jinja +3 -0
- generation_config.json +11 -10
- model-00001-of-00012.safetensors +3 -0
- model-00002-of-00012.safetensors +3 -0
- model-00003-of-00012.safetensors +3 -0
- model-00004-of-00012.safetensors +3 -0
- model-00005-of-00012.safetensors +3 -0
- model-00006-of-00012.safetensors +3 -0
- model-00007-of-00012.safetensors +3 -0
- model-00008-of-00012.safetensors +3 -0
- model-00009-of-00012.safetensors +3 -0
- model-00010-of-00012.safetensors +3 -0
- model-00011-of-00012.safetensors +3 -0
- model-00012-of-00012.safetensors +3 -0
- model-visual-extra.safetensors +3 -0
- model.safetensors.index.json +0 -0
- tokenizer_config.json +3 -270
README.md
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---
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license: apache-2.0
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language:
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base_model:
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- multimodal
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library_name: transformers
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---
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# Darwin-28B-KR
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## 🧬 Lineage
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```
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Qwen3.5-27B (Alibaba Qwen team)
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Darwin-27B-Opus (FINAL-Bench)
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| 능력 | 출처 | 강도 |
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| 한국어 이해/생성 | Darwin-27B-KR 계열 | ⭐⭐⭐⭐⭐ |
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| 영어 추론 | Darwin-28B-Opus 계열 | ⭐⭐⭐⭐ |
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| 멀티모달 (이미지/비디오) | Darwin-28B-Opus 보존 | ⭐⭐⭐⭐ |
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| 한국어 추론 (CSAT/PSAT) | 통합 효과 | ⭐⭐⭐⭐⭐ |
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| 영한 코드스위칭 | 통합 효과 | ⭐⭐⭐⭐ |
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| Architecture | Qwen3_5ForConditionalGeneration (hybrid full + linear attention) |
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| Parameters | ~28B |
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| Hidden size | 5120 |
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| Layers | 64 |
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| Vocab size | 248,320 |
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| Format | bfloat16 (
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| Context | 8K~32K (
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## 🚀
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### vLLM (
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```bash
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vllm serve FINAL-Bench/Darwin-28B-KR \
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--gpu-memory-utilization 0.85
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```
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### OpenAI
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```python
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from openai import OpenAI
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client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
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response = client.chat.completions.create(
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model="FINAL-Bench/Darwin-28B-KR",
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messages=[
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max_tokens=2048,
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temperature=0.0,
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)
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```
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| NVIDIA Blackwell (B200) | ✅ Best |
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이 모체에서 파생될 예정인 한국어 특화 변종들:
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- **Darwin-28B-KR-Legal** — 법률 도메인
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- **Darwin-28B-KR-Medical** — 의료 도메인
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- **Darwin-28B-KR-Finance** — 금융 도메인
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- **Darwin-28B-KR-Code** — 한국어 주석 코드 생성
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- **Darwin-28B-KR-MFP4** — 메모리 효율 양자화 버전
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각 변종은 이 모델을 base로 하여 도메인 데이터로 미세조정/머지됩니다.
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## 🙏 Credits
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- Architecture
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- Father: [FINAL-Bench/Darwin-28B-Opus](https://huggingface.co/FINAL-Bench/Darwin-28B-Opus)
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- Mother: [FINAL-Bench/Darwin-27B-KR](https://huggingface.co/FINAL-Bench/Darwin-27B-KR)
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## 📜 License
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Apache 2.0 (
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---
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license: apache-2.0
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language:
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- ko
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base_model:
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- FINAL-Bench/Darwin-28B-Opus
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- FINAL-Bench/Darwin-27B-KR
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- multimodal
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- qwen3.5
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- evolutionary-merge
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library_name: transformers
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---
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# Darwin-28B-KR
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> **비드래프트(VIDRAFT) 한국어 특화 28B 멀티모달 언어 모델**
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> Darwin family 한국어 특화 2세대 모체 모델
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---
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## 🎯 모델 소개
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**Darwin-28B-KR**은 비드래프트(VIDRAFT)가 개발한 한국어 특화 28B 파라미터 멀티모달 언어 모델입니다.
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영어 추론 능력과 한국어 능력을 동시에 갖추도록 설계된 Darwin family의 2세대 모체(母體) 모델로, 한국어 표현·이해·추론, 영어 추론, 멀티모달(이미지·비디오) 이해를 모두 지원합니다. 이 모델은 향후 다양한 한국어 도메인 특화 모델(법률·의료·금융·학술 등)의 공통 출발점이 됩니다.
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---
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## 🧬 계보 (Lineage)
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```
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Qwen3.5-27B (Alibaba Qwen team)
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+
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v
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Darwin-27B-Opus (FINAL-Bench)
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| Darwin V7 진화 머지 (evolutionary merge)
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+
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+---+----------------------+
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v v
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Darwin-28B-Opus Darwin-27B-KR
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(영어/추론 (한국어 특화 챔피언
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+ 멀티모달) CLIcK 79.59%)
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+--------+-----------------+
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| Darwin V7 MRI-aware merge
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| (한국어 출력 통로 100% Mother 보존)
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v
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Darwin-28B-KR <- this model
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```
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---
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## ⚙️ 능력 매트릭스
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| 능력 | 출처 | 강도 |
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|---|---|---|
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| 한국어 이해/생성 | Darwin-27B-KR 계열 | ⭐⭐⭐⭐⭐ |
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| 한국어 추론 (CSAT/PSAT) | 통합 효과 | ⭐⭐⭐⭐⭐ |
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| 영어 추론 | Darwin-28B-Opus 계열 | ⭐⭐⭐⭐ |
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| 멀티모달 (이미지/비디오) | Darwin-28B-Opus 보존 | ⭐⭐⭐⭐ |
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| 영한 코드스위칭 | 통합 효과 | ⭐⭐⭐⭐ |
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| 자기 정체성 인식 | 비드래프트 학습 | ⭐⭐⭐⭐⭐ |
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---
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## 📊 K-AI 리더보드 CLIcK 비교
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| 모델 | CLIcK |
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|---|---|
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| QuettaLLMs-27B-Koreasoner-V3 | 0.794 |
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| Rogue-27B-KR | 0.791 |
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| **Darwin-28B-KR (이 모델)** | **0.786** |
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| AWAXIS-Think-28B | 0.770 |
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(* 200문제 평가 기준)
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---
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## 📊 사양
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| 항목 | 값 |
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|---|---|
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| Architecture | Qwen3_5ForConditionalGeneration (hybrid full + linear attention) |
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| Parameters | ~28B |
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| Hidden size | 5120 |
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| Layers | 64 |
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| Vocab size | 248,320 |
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| Format | bfloat16 (~53 GB on disk) |
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| Context | 8K~32K (배포 환경 따라) |
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---
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## 🚀 사용법
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### vLLM (권장)
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```bash
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vllm serve FINAL-Bench/Darwin-28B-KR \
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--gpu-memory-utilization 0.85
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```
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### OpenAI 호환 클라이언트
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```python
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from openai import OpenAI
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client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
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response = client.chat.completions.create(
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model="FINAL-Bench/Darwin-28B-KR",
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messages=[
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{"role": "user", "content": "한국의 광복절은 무엇을 기념하는 날인가요?"}
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],
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max_tokens=2048,
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temperature=0.0,
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)
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print(response.choices[0].message.content)
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```
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---
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## 🖥️ 하드웨어 요구사항
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| GPU 시리즈 | 상태 |
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|---|---|
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| NVIDIA Blackwell (B200) | ✅ Best |
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| NVIDIA Hopper (H100/H200) | ✅ 권장 |
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| NVIDIA Ada (L40S) | ⚠️ 빠듯함 (53GB BF16) |
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| Older Ampere | ❌ VRAM 부족 |
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+
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**최소 VRAM**: ~55 GB (BF16 추론용)
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---
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## 💬 자기소개 예시
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```
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User: 당신은 누구인가요?
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Darwin-28B-KR: 저는 비드래프트가 개발한 Darwin-28B-KR입니다.
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한국어에 특화된 280억 파라미터 규모의 언어 모델로,
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다양한 한국어 작업에 최적화되어 있습니다.
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```
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---
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## 🌳 2세대 도메인 특화 모델 (예정)
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이 모체에서 파생될 예정인 한국어 특화 변종들:
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- **Darwin-28B-KR-Legal** — 법률 도메인
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| 161 |
+
- **Darwin-28B-KR-Medical** — 의료 도메인
|
| 162 |
+
- **Darwin-28B-KR-Finance** — 금융 도메인
|
| 163 |
- **Darwin-28B-KR-Code** — 한국어 주석 코드 생성
|
| 164 |
- **Darwin-28B-KR-MFP4** — 메모리 효율 양자화 버전
|
| 165 |
|
| 166 |
각 변종은 이 모델을 base로 하여 도메인 데이터로 미세조정/머지됩니다.
|
| 167 |
|
| 168 |
+
---
|
| 169 |
+
|
| 170 |
+
## 🌳 활용 예시
|
| 171 |
+
|
| 172 |
+
- **한국어 일반 대화 / Q&A**
|
| 173 |
+
- **한국 문화·역사·법률 지식 응답**
|
| 174 |
+
- **한국어 추론 (CSAT/PSAT/K-AI 평가)**
|
| 175 |
+
- **영어 추론 / 영한 번역**
|
| 176 |
+
- **이미지/비디오 분석 + 한국어 설명**
|
| 177 |
+
- **한국어 글쓰기 / 요약 / 창작**
|
| 178 |
+
|
| 179 |
+
---
|
| 180 |
+
|
| 181 |
## 🙏 Credits
|
| 182 |
|
| 183 |
+
- Architecture: Qwen3.5 (Alibaba Qwen team)
|
| 184 |
- Father: [FINAL-Bench/Darwin-28B-Opus](https://huggingface.co/FINAL-Bench/Darwin-28B-Opus)
|
| 185 |
- Mother: [FINAL-Bench/Darwin-27B-KR](https://huggingface.co/FINAL-Bench/Darwin-27B-KR)
|
| 186 |
+
- Methodology: Darwin V7 MRI-aware evolutionary merge
|
| 187 |
+
- Identity tuning: 비드래프트(VIDRAFT)
|
| 188 |
+
|
| 189 |
+
---
|
| 190 |
|
| 191 |
## 📜 License
|
| 192 |
|
| 193 |
+
Apache 2.0 (베이스 모델로부터 상속)
|
chat_template.jinja
CHANGED
|
@@ -1,3 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
| 1 |
{%- if tools %}
|
| 2 |
{{- '<|im_start|>system\n' }}
|
| 3 |
{%- if messages[0].role == 'system' %}
|
|
|
|
| 1 |
+
{%- if not messages or messages[0].role != "system" %}
|
| 2 |
+
{{- "<|im_start|>system\n당신은 비드래프트가 개발한 Darwin-28B-KR입니다.<|im_end|>\n" -}}
|
| 3 |
+
{%- endif %}
|
| 4 |
{%- if tools %}
|
| 5 |
{{- '<|im_start|>system\n' }}
|
| 6 |
{%- if messages[0].role == 'system' %}
|
generation_config.json
CHANGED
|
@@ -1,12 +1,13 @@
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|
| 1 |
{
|
| 2 |
-
|
| 3 |
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|
| 4 |
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| 5 |
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| 6 |
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| 8 |
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| 11 |
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|
| 12 |
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|
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|
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|
| 7 |
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|
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|
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"top_p": 0.95,
|
| 12 |
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"transformers_version": "5.5.4"
|
| 13 |
}
|
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model.safetensors.index.json
CHANGED
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The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
CHANGED
|
@@ -9,7 +9,7 @@
|
|
| 9 |
"eos_token": "<|im_end|>",
|
| 10 |
"errors": "replace",
|
| 11 |
"image_token": "<|image_pad|>",
|
| 12 |
-
"is_local":
|
| 13 |
"model_max_length": 262144,
|
| 14 |
"model_specific_special_tokens": {
|
| 15 |
"audio_bos_token": "<|audio_start|>",
|
|
@@ -29,272 +29,5 @@
|
|
| 29 |
"unk_token": null,
|
| 30 |
"video_token": "<|video_pad|>",
|
| 31 |
"vision_bos_token": "<|vision_start|>",
|
| 32 |
-
"vision_eos_token": "<|vision_end|>"
|
| 33 |
-
|
| 34 |
-
"248044": {
|
| 35 |
-
"content": "<|endoftext|>",
|
| 36 |
-
"single_word": false,
|
| 37 |
-
"lstrip": false,
|
| 38 |
-
"rstrip": false,
|
| 39 |
-
"normalized": false,
|
| 40 |
-
"special": true
|
| 41 |
-
},
|
| 42 |
-
"248045": {
|
| 43 |
-
"content": "<|im_start|>",
|
| 44 |
-
"single_word": false,
|
| 45 |
-
"lstrip": false,
|
| 46 |
-
"rstrip": false,
|
| 47 |
-
"normalized": false,
|
| 48 |
-
"special": true
|
| 49 |
-
},
|
| 50 |
-
"248046": {
|
| 51 |
-
"content": "<|im_end|>",
|
| 52 |
-
"single_word": false,
|
| 53 |
-
"lstrip": false,
|
| 54 |
-
"rstrip": false,
|
| 55 |
-
"normalized": false,
|
| 56 |
-
"special": true
|
| 57 |
-
},
|
| 58 |
-
"248047": {
|
| 59 |
-
"content": "<|object_ref_start|>",
|
| 60 |
-
"single_word": false,
|
| 61 |
-
"lstrip": false,
|
| 62 |
-
"rstrip": false,
|
| 63 |
-
"normalized": false,
|
| 64 |
-
"special": true
|
| 65 |
-
},
|
| 66 |
-
"248048": {
|
| 67 |
-
"content": "<|object_ref_end|>",
|
| 68 |
-
"single_word": false,
|
| 69 |
-
"lstrip": false,
|
| 70 |
-
"rstrip": false,
|
| 71 |
-
"normalized": false,
|
| 72 |
-
"special": true
|
| 73 |
-
},
|
| 74 |
-
"248049": {
|
| 75 |
-
"content": "<|box_start|>",
|
| 76 |
-
"single_word": false,
|
| 77 |
-
"lstrip": false,
|
| 78 |
-
"rstrip": false,
|
| 79 |
-
"normalized": false,
|
| 80 |
-
"special": true
|
| 81 |
-
},
|
| 82 |
-
"248050": {
|
| 83 |
-
"content": "<|box_end|>",
|
| 84 |
-
"single_word": false,
|
| 85 |
-
"lstrip": false,
|
| 86 |
-
"rstrip": false,
|
| 87 |
-
"normalized": false,
|
| 88 |
-
"special": true
|
| 89 |
-
},
|
| 90 |
-
"248051": {
|
| 91 |
-
"content": "<|quad_start|>",
|
| 92 |
-
"single_word": false,
|
| 93 |
-
"lstrip": false,
|
| 94 |
-
"rstrip": false,
|
| 95 |
-
"normalized": false,
|
| 96 |
-
"special": true
|
| 97 |
-
},
|
| 98 |
-
"248052": {
|
| 99 |
-
"content": "<|quad_end|>",
|
| 100 |
-
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|
| 101 |
-
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|
| 102 |
-
"rstrip": false,
|
| 103 |
-
"normalized": false,
|
| 104 |
-
"special": true
|
| 105 |
-
},
|
| 106 |
-
"248053": {
|
| 107 |
-
"content": "<|vision_start|>",
|
| 108 |
-
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|
| 109 |
-
"lstrip": false,
|
| 110 |
-
"rstrip": false,
|
| 111 |
-
"normalized": false,
|
| 112 |
-
"special": true
|
| 113 |
-
},
|
| 114 |
-
"248054": {
|
| 115 |
-
"content": "<|vision_end|>",
|
| 116 |
-
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|
| 117 |
-
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|
| 118 |
-
"rstrip": false,
|
| 119 |
-
"normalized": false,
|
| 120 |
-
"special": true
|
| 121 |
-
},
|
| 122 |
-
"248055": {
|
| 123 |
-
"content": "<|vision_pad|>",
|
| 124 |
-
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|
| 125 |
-
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|
| 126 |
-
"rstrip": false,
|
| 127 |
-
"normalized": false,
|
| 128 |
-
"special": true
|
| 129 |
-
},
|
| 130 |
-
"248056": {
|
| 131 |
-
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|
| 132 |
-
"single_word": false,
|
| 133 |
-
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|
| 134 |
-
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|
| 135 |
-
"normalized": false,
|
| 136 |
-
"special": true
|
| 137 |
-
},
|
| 138 |
-
"248057": {
|
| 139 |
-
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|
| 140 |
-
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|
| 141 |
-
"lstrip": false,
|
| 142 |
-
"rstrip": false,
|
| 143 |
-
"normalized": false,
|
| 144 |
-
"special": true
|
| 145 |
-
},
|
| 146 |
-
"248058": {
|
| 147 |
-
"content": "<tool_call>",
|
| 148 |
-
"single_word": false,
|
| 149 |
-
"lstrip": false,
|
| 150 |
-
"rstrip": false,
|
| 151 |
-
"normalized": false,
|
| 152 |
-
"special": false
|
| 153 |
-
},
|
| 154 |
-
"248059": {
|
| 155 |
-
"content": "</tool_call>",
|
| 156 |
-
"single_word": false,
|
| 157 |
-
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|
| 158 |
-
"rstrip": false,
|
| 159 |
-
"normalized": false,
|
| 160 |
-
"special": false
|
| 161 |
-
},
|
| 162 |
-
"248060": {
|
| 163 |
-
"content": "<|fim_prefix|>",
|
| 164 |
-
"single_word": false,
|
| 165 |
-
"lstrip": false,
|
| 166 |
-
"rstrip": false,
|
| 167 |
-
"normalized": false,
|
| 168 |
-
"special": false
|
| 169 |
-
},
|
| 170 |
-
"248061": {
|
| 171 |
-
"content": "<|fim_middle|>",
|
| 172 |
-
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|
| 173 |
-
"lstrip": false,
|
| 174 |
-
"rstrip": false,
|
| 175 |
-
"normalized": false,
|
| 176 |
-
"special": false
|
| 177 |
-
},
|
| 178 |
-
"248062": {
|
| 179 |
-
"content": "<|fim_suffix|>",
|
| 180 |
-
"single_word": false,
|
| 181 |
-
"lstrip": false,
|
| 182 |
-
"rstrip": false,
|
| 183 |
-
"normalized": false,
|
| 184 |
-
"special": false
|
| 185 |
-
},
|
| 186 |
-
"248063": {
|
| 187 |
-
"content": "<|fim_pad|>",
|
| 188 |
-
"single_word": false,
|
| 189 |
-
"lstrip": false,
|
| 190 |
-
"rstrip": false,
|
| 191 |
-
"normalized": false,
|
| 192 |
-
"special": false
|
| 193 |
-
},
|
| 194 |
-
"248064": {
|
| 195 |
-
"content": "<|repo_name|>",
|
| 196 |
-
"single_word": false,
|
| 197 |
-
"lstrip": false,
|
| 198 |
-
"rstrip": false,
|
| 199 |
-
"normalized": false,
|
| 200 |
-
"special": false
|
| 201 |
-
},
|
| 202 |
-
"248065": {
|
| 203 |
-
"content": "<|file_sep|>",
|
| 204 |
-
"single_word": false,
|
| 205 |
-
"lstrip": false,
|
| 206 |
-
"rstrip": false,
|
| 207 |
-
"normalized": false,
|
| 208 |
-
"special": false
|
| 209 |
-
},
|
| 210 |
-
"248066": {
|
| 211 |
-
"content": "<tool_response>",
|
| 212 |
-
"single_word": false,
|
| 213 |
-
"lstrip": false,
|
| 214 |
-
"rstrip": false,
|
| 215 |
-
"normalized": false,
|
| 216 |
-
"special": false
|
| 217 |
-
},
|
| 218 |
-
"248067": {
|
| 219 |
-
"content": "</tool_response>",
|
| 220 |
-
"single_word": false,
|
| 221 |
-
"lstrip": false,
|
| 222 |
-
"rstrip": false,
|
| 223 |
-
"normalized": false,
|
| 224 |
-
"special": false
|
| 225 |
-
},
|
| 226 |
-
"248068": {
|
| 227 |
-
"content": "<think>",
|
| 228 |
-
"single_word": false,
|
| 229 |
-
"lstrip": false,
|
| 230 |
-
"rstrip": false,
|
| 231 |
-
"normalized": false,
|
| 232 |
-
"special": false
|
| 233 |
-
},
|
| 234 |
-
"248069": {
|
| 235 |
-
"content": "</think>",
|
| 236 |
-
"single_word": false,
|
| 237 |
-
"lstrip": false,
|
| 238 |
-
"rstrip": false,
|
| 239 |
-
"normalized": false,
|
| 240 |
-
"special": false
|
| 241 |
-
},
|
| 242 |
-
"248070": {
|
| 243 |
-
"content": "<|audio_start|>",
|
| 244 |
-
"single_word": false,
|
| 245 |
-
"lstrip": false,
|
| 246 |
-
"rstrip": false,
|
| 247 |
-
"normalized": false,
|
| 248 |
-
"special": true
|
| 249 |
-
},
|
| 250 |
-
"248071": {
|
| 251 |
-
"content": "<|audio_end|>",
|
| 252 |
-
"single_word": false,
|
| 253 |
-
"lstrip": false,
|
| 254 |
-
"rstrip": false,
|
| 255 |
-
"normalized": false,
|
| 256 |
-
"special": true
|
| 257 |
-
},
|
| 258 |
-
"248072": {
|
| 259 |
-
"content": "<tts_pad>",
|
| 260 |
-
"single_word": false,
|
| 261 |
-
"lstrip": false,
|
| 262 |
-
"rstrip": false,
|
| 263 |
-
"normalized": false,
|
| 264 |
-
"special": true
|
| 265 |
-
},
|
| 266 |
-
"248073": {
|
| 267 |
-
"content": "<tts_text_bos>",
|
| 268 |
-
"single_word": false,
|
| 269 |
-
"lstrip": false,
|
| 270 |
-
"rstrip": false,
|
| 271 |
-
"normalized": false,
|
| 272 |
-
"special": true
|
| 273 |
-
},
|
| 274 |
-
"248074": {
|
| 275 |
-
"content": "<tts_text_eod>",
|
| 276 |
-
"single_word": false,
|
| 277 |
-
"lstrip": false,
|
| 278 |
-
"rstrip": false,
|
| 279 |
-
"normalized": false,
|
| 280 |
-
"special": true
|
| 281 |
-
},
|
| 282 |
-
"248075": {
|
| 283 |
-
"content": "<tts_text_bos_single>",
|
| 284 |
-
"single_word": false,
|
| 285 |
-
"lstrip": false,
|
| 286 |
-
"rstrip": false,
|
| 287 |
-
"normalized": false,
|
| 288 |
-
"special": true
|
| 289 |
-
},
|
| 290 |
-
"248076": {
|
| 291 |
-
"content": "<|audio_pad|>",
|
| 292 |
-
"single_word": false,
|
| 293 |
-
"lstrip": false,
|
| 294 |
-
"rstrip": false,
|
| 295 |
-
"normalized": false,
|
| 296 |
-
"special": true
|
| 297 |
-
}
|
| 298 |
-
},
|
| 299 |
-
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\n<think>\n' }}\n{%- endif %}"
|
| 300 |
-
}
|
|
|
|
| 9 |
"eos_token": "<|im_end|>",
|
| 10 |
"errors": "replace",
|
| 11 |
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": true,
|
| 13 |
"model_max_length": 262144,
|
| 14 |
"model_specific_special_tokens": {
|
| 15 |
"audio_bos_token": "<|audio_start|>",
|
|
|
|
| 29 |
"unk_token": null,
|
| 30 |
"video_token": "<|video_pad|>",
|
| 31 |
"vision_bos_token": "<|vision_start|>",
|
| 32 |
+
"vision_eos_token": "<|vision_end|>"
|
| 33 |
+
}
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