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bigcode
/
tiny_starcoder_py

Text Generation
Transformers
PyTorch
Safetensors
gpt_bigcode
code
Eval Results (legacy)
text-generation-inference
Model card Files Files and versions
xet
Community
10

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

  • Libraries
  • Transformers

    How to use bigcode/tiny_starcoder_py with Transformers:

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

    How to use bigcode/tiny_starcoder_py with vLLM:

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

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

    How to use bigcode/tiny_starcoder_py with Docker Model Runner:

    docker model run hf.co/bigcode/tiny_starcoder_py
tiny_starcoder_py
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  • 3 contributors
History: 9 commits
loubnabnl's picture
loubnabnl HF Staff
Update README.md
b2b9a68 almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • README.md
    3.01 kB
    Update README.md almost 3 years ago
  • config.json
    1.03 kB
    Update config.json almost 3 years ago
  • generation_config.json
    111 Bytes
    Update generation_config.json almost 3 years ago
  • merges.txt
    442 kB
    add tokenizer almost 3 years ago
  • pytorch_model.bin
    657 MB
    xet
    iter_0050000 almost 3 years ago
  • special_tokens_map.json
    532 Bytes
    add tokenizer almost 3 years ago
  • tokenizer.json
    2.06 MB
    add tokenizer almost 3 years ago
  • tokenizer_config.json
    677 Bytes
    add tokenizer almost 3 years ago
  • vocab.json
    777 kB
    add tokenizer almost 3 years ago