Darwin-9B-NEG

Instructions to use ansulev/Darwin-9B-NEG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ansulev/Darwin-9B-NEG with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ansulev/Darwin-9B-NEG")
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("ansulev/Darwin-9B-NEG")
model = AutoModelForImageTextToText.from_pretrained("ansulev/Darwin-9B-NEG")
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 ansulev/Darwin-9B-NEG with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ansulev/Darwin-9B-NEG"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ansulev/Darwin-9B-NEG",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ansulev/Darwin-9B-NEG

SGLang

How to use ansulev/Darwin-9B-NEG 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 "ansulev/Darwin-9B-NEG" \
    --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": "ansulev/Darwin-9B-NEG",
		"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 "ansulev/Darwin-9B-NEG" \
        --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": "ansulev/Darwin-9B-NEG",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ansulev/Darwin-9B-NEG with Docker Model Runner:
```
docker model run hf.co/ansulev/Darwin-9B-NEG
```

Darwin-9B-NEG

File size: 2,902 Bytes

28767b8

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  "architectures": [
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  "image_token_id": 248056,
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  "text_config": {
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    "attention_dropout": 0.0,
    "attn_output_gate": true,
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    "hidden_act": "silu",
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    "layer_types": [
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    "linear_key_head_dim": 128,
    "linear_num_key_heads": 16,
    "linear_num_value_heads": 32,
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    "mlp_only_layers": [],
    "model_type": "qwen3_5_text",
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    "rms_norm_eps": 1e-06,
    "use_cache": true,
    "vocab_size": 248320,
    "mamba_ssm_dtype": "float32",
    "rope_parameters": {
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      "rope_type": "default",
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  "vision_config": {
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    "depth": 27,
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    "temporal_patch_size": 2
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  "vision_end_token_id": 248054,
  "vision_start_token_id": 248053,
  "neg_config": {
    "enabled": true,
    "threshold": 1.175187349319458,
    "top_k": 20,
    "version": "1.0",
    "base_eval_pearson": 0.8744,
    "hidden_size_for_head": 4096
  },
  "_darwin_v8": "Darwin-9B-NEG (Native Entropy Gating)"
}