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IndianChess
/
Therapy-Alpaca

Text Generation
Transformers
TensorBoard
Safetensors
gpt2
Generated from Trainer
text-generation-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use IndianChess/Therapy-Alpaca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use IndianChess/Therapy-Alpaca with Transformers:

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

    How to use IndianChess/Therapy-Alpaca with vLLM:

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

    How to use IndianChess/Therapy-Alpaca 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 "IndianChess/Therapy-Alpaca" \
        --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": "IndianChess/Therapy-Alpaca",
    		"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 "IndianChess/Therapy-Alpaca" \
            --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": "IndianChess/Therapy-Alpaca",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use IndianChess/Therapy-Alpaca with Docker Model Runner:

    docker model run hf.co/IndianChess/Therapy-Alpaca
Therapy-Alpaca / runs
76.9 kB
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  • 1 contributor
History: 66 commits
Ish Man
Training in progress, step 16500
6d376a7 verified about 2 years ago
  • Jun26_22-56-12_ea89367acdfc
    End of training about 2 years ago
  • Jun26_22-58-24_ea89367acdfc
    End of training about 2 years ago
  • Jun26_22-59-58_ea89367acdfc
    End of training about 2 years ago
  • Jun26_23-02-45_ea89367acdfc
    End of training about 2 years ago
  • Jun26_23-04-38_ea89367acdfc
    End of training about 2 years ago
  • Jun27_01-03-49_4f946d7dbb25
    End of training about 2 years ago
  • Jun27_01-48-31_4f946d7dbb25
    End of training about 2 years ago
  • Jun27_02-22-38_4f946d7dbb25
    End of training about 2 years ago
  • Jun27_02-48-34_4f946d7dbb25
    End of training about 2 years ago
  • Jun27_13-25-48_2d60a11a839d
    Training in progress, step 3500 about 2 years ago
  • Jun27_21-57-35_bc1c6492eba5
    Training in progress, step 16500 about 2 years ago