Instructions to use FINAL-Bench/Darwin-28B-NEG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FINAL-Bench/Darwin-28B-NEG with Transformers:

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

pipe = pipeline("text-generation", model="FINAL-Bench/Darwin-28B-NEG")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FINAL-Bench/Darwin-28B-NEG")
model = AutoModelForCausalLM.from_pretrained("FINAL-Bench/Darwin-28B-NEG", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FINAL-Bench/Darwin-28B-NEG 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-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": "FINAL-Bench/Darwin-28B-NEG",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FINAL-Bench/Darwin-28B-NEG

SGLang

How to use FINAL-Bench/Darwin-28B-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 "FINAL-Bench/Darwin-28B-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": "FINAL-Bench/Darwin-28B-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 "FINAL-Bench/Darwin-28B-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": "FINAL-Bench/Darwin-28B-NEG",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FINAL-Bench/Darwin-28B-NEG with Docker Model Runner:
```
docker model run hf.co/FINAL-Bench/Darwin-28B-NEG
```

Darwin-28B-NEG / chat_template.jinja

SeaWolf-AI

Initial Darwin-28B-NEG release (base + NEG-Head + NEG-Gate)

c3d7133 verified 3 months ago

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	{%- if not messages %}
	{{- raise_exception('No messages provided.') }}
	{%- endif %}
	{%- if tools and tools is iterable and tools is not mapping %}
	{{- '<\|im_start\|>system
	' }}
	{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
	{%- for tool in tools %}
	{{- "\n" }}
	{{- tool \| tojson }}
	{%- endfor %}
	{{- "\n</tools>" }}
	{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format\n- Required parameters MUST be specified\n- If there is no function call available, answer normally\n</IMPORTANT>' }}
	{%- if messages[0].role == 'system' %}
	{{- '\n\n' + messages[0].content \| trim + '<\|im_end\|>\n' }}
	{%- else %}
	{{- '<\|im_end\|>\n' }}
	{%- endif %}
	{%- else %}
	{%- if messages[0].role == 'system' %}
	{{- '<\|im_start\|>system\n' + messages[0].content \| trim + '<\|im_end\|>\n' }}
	{%- endif %}
	{%- endif %}
	{%- set ns = namespace(last_query_index=messages\|length - 1) %}
	{%- for message in messages %}
	{%- if message.role == "user" %}
	{{- '<\|im_start\|>user\n' + message.content \| trim + '<\|im_end\|>\n' }}
	{%- elif message.role == "assistant" %}
	{%- set content = message.content \| trim %}
	{%- set reasoning = '' %}
	{%- if '</think>' in content %}
	{%- set reasoning = content.split('</think>')[0].split('<think>')[-1].strip() %}
	{%- set content = content.split('</think>')[-1].strip() %}
	{%- endif %}
	{{- '<\|im_start\|>assistant\n' }}
	{%- if reasoning %}
	{{- '<think>\n' + reasoning + '\n</think>\n\n' }}
	{%- endif %}
	{{- content + '<\|im_end\|>\n' }}
	{%- elif message.role == "tool" %}
	{{- '<tool_response>\n' + message.content \| trim + '\n</tool_response>\n' }}
	{%- endif %}
	{%- endfor %}
	{%- if add_generation_prompt %}
	{{- '<\|im_start\|>assistant\n<think>\n' }}
	{%- endif %}