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Pplus
/
mistral-health-faq

Text Generation
Transformers
Safetensors
Burmese
mistral
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use Pplus/mistral-health-faq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Pplus/mistral-health-faq with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Pplus/mistral-health-faq")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("Pplus/mistral-health-faq")
    model = AutoModelForCausalLM.from_pretrained("Pplus/mistral-health-faq")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Pplus/mistral-health-faq with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Pplus/mistral-health-faq"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Pplus/mistral-health-faq",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Pplus/mistral-health-faq
  • SGLang

    How to use Pplus/mistral-health-faq 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 "Pplus/mistral-health-faq" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Pplus/mistral-health-faq",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    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 "Pplus/mistral-health-faq" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Pplus/mistral-health-faq",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Pplus/mistral-health-faq with Docker Model Runner:

    docker model run hf.co/Pplus/mistral-health-faq
mistral-health-faq
29.7 GB
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  • 1 contributor
History: 11 commits
Pplus's picture
Pplus
Update README.md
8db39d5 verified over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    5.19 kB
    Update README.md over 2 years ago
  • adapter_config.json
    693 Bytes
    Upload model over 2 years ago
  • adapter_model.safetensors
    694 MB
    xet
    Upload model over 2 years ago
  • config.json
    613 Bytes
    Upload MistralForCausalLM over 2 years ago
  • model-00001-of-00006.safetensors
    4.99 GB
    xet
    Upload MistralForCausalLM over 2 years ago
  • model-00002-of-00006.safetensors
    4.9 GB
    xet
    Upload MistralForCausalLM over 2 years ago
  • model-00003-of-00006.safetensors
    5 GB
    xet
    Upload MistralForCausalLM over 2 years ago
  • model-00004-of-00006.safetensors
    5 GB
    xet
    Upload MistralForCausalLM over 2 years ago
  • model-00005-of-00006.safetensors
    4.83 GB
    xet
    Upload MistralForCausalLM over 2 years ago
  • model-00006-of-00006.safetensors
    4.25 GB
    xet
    Upload MistralForCausalLM over 2 years ago
  • model.safetensors.index.json
    24 kB
    Upload MistralForCausalLM over 2 years ago
  • special_tokens_map.json
    437 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    1.8 MB
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  • tokenizer.model
    493 kB
    xet
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  • tokenizer_config.json
    918 Bytes
    Upload tokenizer over 2 years ago