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not-lain
/
PyGPT

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

Instructions to use not-lain/PyGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use not-lain/PyGPT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="not-lain/PyGPT")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("not-lain/PyGPT")
    model = AutoModelForCausalLM.from_pretrained("not-lain/PyGPT")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use not-lain/PyGPT with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "not-lain/PyGPT"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "not-lain/PyGPT",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/not-lain/PyGPT
  • SGLang

    How to use not-lain/PyGPT 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 "not-lain/PyGPT" \
        --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": "not-lain/PyGPT",
    		"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 "not-lain/PyGPT" \
            --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": "not-lain/PyGPT",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use not-lain/PyGPT with Docker Model Runner:

    docker model run hf.co/not-lain/PyGPT
PyGPT
501 MB
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  • 1 contributor
History: 23 commits
not-lain's picture
not-lain
Update README.md
5c49efd verified over 2 years ago
  • runs
    Training in progress, step 9000 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    1.62 kB
    Update README.md over 2 years ago
  • config.json
    907 Bytes
    Training in progress, step 500 over 2 years ago
  • merges.txt
    456 kB
    Upload tokenizer over 2 years ago
  • model.safetensors
    498 MB
    xet
    Training in progress, step 9000 over 2 years ago
  • special_tokens_map.json
    131 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    2.11 MB
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    476 Bytes
    Upload tokenizer over 2 years ago
  • training_args.bin

    Detected Pickle imports (8)

    • "transformers.trainer_utils.IntervalStrategy",
    • "transformers.training_args.TrainingArguments",
    • "torch.device",
    • "transformers.trainer_utils.SchedulerType",
    • "transformers.training_args.OptimizerNames",
    • "accelerate.utils.dataclasses.DistributedType",
    • "transformers.trainer_utils.HubStrategy",
    • "accelerate.state.PartialState"

    How to fix it?

    4.54 kB
    xet
    Training in progress, step 500 over 2 years ago
  • vocab.json
    798 kB
    Upload tokenizer over 2 years ago