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menesnas
/
ChatTemplate

Text Generation
Transformers
Turkish
English
chat-template
jinja2
prompt-format
pharmacy
tool-calling
rag
conversational
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use menesnas/ChatTemplate with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="menesnas/ChatTemplate")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("menesnas/ChatTemplate", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use menesnas/ChatTemplate with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "menesnas/ChatTemplate"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "menesnas/ChatTemplate",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/menesnas/ChatTemplate
  • SGLang

    How to use menesnas/ChatTemplate 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 "menesnas/ChatTemplate" \
        --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": "menesnas/ChatTemplate",
    		"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 "menesnas/ChatTemplate" \
            --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": "menesnas/ChatTemplate",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use menesnas/ChatTemplate with Docker Model Runner:

    docker model run hf.co/menesnas/ChatTemplate
ChatTemplate
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  • 1 contributor
History: 3 commits
menesnas's picture
menesnas
Update README.md
880081f verified 2 days ago
  • .gitattributes
    1.52 kB
    initial commit 2 days ago
  • README.md
    4.83 kB
    Update README.md 2 days ago
  • chat_template.jinja
    2.38 kB
    Upload folder using huggingface_hub 2 days ago
  • main.py
    4.45 kB
    Upload folder using huggingface_hub 2 days ago