Text Generation
Transformers
Safetensors
gemma4
image-text-to-text
darwin-v6
generation-2
evolutionary-merge
mri-guided
dare-ties
reasoning
thinking
proto-agi
vidraft
conversational
Instructions to use FINAL-Bench/Darwin-4B-David with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FINAL-Bench/Darwin-4B-David with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FINAL-Bench/Darwin-4B-David") 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-4B-David") model = AutoModelForImageTextToText.from_pretrained("FINAL-Bench/Darwin-4B-David") 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-4B-David with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FINAL-Bench/Darwin-4B-David" # 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-4B-David", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/FINAL-Bench/Darwin-4B-David
- SGLang
How to use FINAL-Bench/Darwin-4B-David 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-4B-David" \ --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-4B-David", "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-4B-David" \ --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-4B-David", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use FINAL-Bench/Darwin-4B-David with Docker Model Runner:
docker model run hf.co/FINAL-Bench/Darwin-4B-David
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# Darwin-4B-David β The First Second-Generation Darwin Model
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> Gemma 4 E4B Dense | 4.5B Params | Thinking Mode | 128K Context | 140+ Languages | BF16 | Apache 2.0
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# Darwin-4B-David β The First Second-Generation Darwin Model
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<p align="center">
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<a href="https://huggingface.co/FINAL-Bench/Darwin-4B-Opus"><img src="https://img.shields.io/badge/π§¬_Gen1-Darwin--4B--Opus-blue?style=for-the-badge" alt="Gen1"></a>
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<a href="https://huggingface.co/FINAL-Bench/Darwin-4B-David"><img src="https://img.shields.io/badge/π§¬_Gen2-Darwin--4B--David-blue?style=for-the-badge" alt="Gen2"></a>
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<a href="https://huggingface.co/FINAL-Bench/Darwin-4B-Genesis"><img src="https://img.shields.io/badge/β_Gen3-Darwin--4B--Genesis-gold?style=for-the-badge" alt="Gen3"></a>
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<a href="https://huggingface.co/FINAL-Bench/Darwin-9B-Opus"><img src="https://img.shields.io/badge/π§¬_Model-Darwin--9B--Opus-blue?style=for-the-badge" alt="9B"></a>
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<a href="https://huggingface.co/spaces/FINAL-Bench/Darwin-9B-Opus"><img src="https://img.shields.io/badge/π_Space-9B_Demo-purple?style=for-the-badge" alt="9B Space"></a>
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<a href="https://huggingface.co/FINAL-Bench/Darwin-31B-Opus"><img src="https://img.shields.io/badge/π§¬_Model-Darwin--31B--Opus-blue?style=for-the-badge" alt="31B"></a>
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<a href="https://huggingface.co/spaces/FINAL-Bench/Darwin-31B-Opus"><img src="https://img.shields.io/badge/π_Space-31B_Demo-purple?style=for-the-badge" alt="31B Space"></a>
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<a href="https://huggingface.co/FINAL-Bench/Darwin-35B-A3B-Opus"><img src="https://img.shields.io/badge/π§¬_Model-Darwin--35B--A3B--Opus-blue?style=for-the-badge" alt="35B"></a>
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<a href="https://huggingface.co/spaces/FINAL-Bench/Darwin-35B-A3B-Opus"><img src="https://img.shields.io/badge/π_Space-35B_Demo-purple?style=for-the-badge" alt="35B Space"></a>
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<a href="https://huggingface.co/FINAL-Bench/Darwin-35B-A3B-Opus-Q8-GGUF"><img src="https://img.shields.io/badge/π¦_GGUF-Q8--Official-yellow?style=for-the-badge" alt="Q8 GGUF"></a>
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<a href="https://huggingface.co/bartowski/FINAL-Bench_Darwin-35B-A3B-Opus-GGUF"><img src="https://img.shields.io/badge/π¦_GGUF-bartowski-yellow?style=for-the-badge" alt="bartowski GGUF"></a>
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<a href="https://huggingface.co/spaces/FINAL-Bench/Leaderboard"><img src="https://img.shields.io/badge/π_FINAL_Bench-Leaderboard-green?style=for-the-badge" alt="FINAL Bench"></a>
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<a href="https://huggingface.co/spaces/FINAL-Bench/all-bench-leaderboard"><img src="https://img.shields.io/badge/π_ALL_Bench-Leaderboard-orange?style=for-the-badge" alt="ALL Bench"></a>
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> Gemma 4 E4B Dense | 4.5B Params | Thinking Mode | 128K Context | 140+ Languages | BF16 | Apache 2.0
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