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loeslab
/
mistral_small_psych

Text Generation
PEFT
Safetensors
Transformers
Spanish
lora
sft
trl
unsloth
psychiatry
spanish
EHR
mental
illness
clinical
symptoms
phenotypes
conversational
Model card Files Files and versions
xet
Community

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

  • Libraries
  • PEFT

    How to use loeslab/mistral_small_psych with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-small-24b-instruct-2501-bnb-4bit")
    model = PeftModel.from_pretrained(base_model, "loeslab/mistral_small_psych")
  • Transformers

    How to use loeslab/mistral_small_psych with Transformers:

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

    How to use loeslab/mistral_small_psych with vLLM:

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

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

    How to use loeslab/mistral_small_psych with Docker Model Runner:

    docker model run hf.co/loeslab/mistral_small_psych
mistral_small_psych
202 MB
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  • 1 contributor
History: 8 commits
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clari1
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