Instructions to use ethanker/lfm2_350m_commit_diff_summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ethanker/lfm2_350m_commit_diff_summarizer with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/LFM2-350M-unsloth-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "ethanker/lfm2_350m_commit_diff_summarizer")

Transformers

How to use ethanker/lfm2_350m_commit_diff_summarizer with Transformers:

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

pipe = pipeline("text-generation", model="ethanker/lfm2_350m_commit_diff_summarizer")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ethanker/lfm2_350m_commit_diff_summarizer", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ethanker/lfm2_350m_commit_diff_summarizer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ethanker/lfm2_350m_commit_diff_summarizer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ethanker/lfm2_350m_commit_diff_summarizer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ethanker/lfm2_350m_commit_diff_summarizer

SGLang

How to use ethanker/lfm2_350m_commit_diff_summarizer 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 "ethanker/lfm2_350m_commit_diff_summarizer" \
    --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": "ethanker/lfm2_350m_commit_diff_summarizer",
		"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 "ethanker/lfm2_350m_commit_diff_summarizer" \
        --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": "ethanker/lfm2_350m_commit_diff_summarizer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ethanker/lfm2_350m_commit_diff_summarizer with Docker Model Runner:
```
docker model run hf.co/ethanker/lfm2_350m_commit_diff_summarizer
```

lfm2_350m_commit_diff_summarizer / chat_template.jinja

ethanker

Add LORA adapter for commit diff summarizer

94a0c59 verified 7 months ago

raw

history blame contribute delete

209 Bytes

	{{bos_token}}{% for message in messages %}{{'<\|im_start\|>' + message['role'] + '
	' + message['content'] + '<\|im_end\|>' + '
	'}}{% endfor %}{% if add_generation_prompt %}{{ '<\|im_start\|>assistant
	' }}{% endif %}

	{{bos_token}}{% for message in messages %}{{'<\|im_start\|>' + message['role'] + '
	' + message['content'] + '<\|im_end\|>' + '
	'}}{% endfor %}{% if add_generation_prompt %}{{ '<\|im_start\|>assistant
	' }}{% endif %}