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PDG
/
gpt2_ft_police_articles

Text Generation
Transformers
PyTorch
TensorBoard
gpt2
Generated from Trainer
text-generation-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use PDG/gpt2_ft_police_articles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use PDG/gpt2_ft_police_articles with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="PDG/gpt2_ft_police_articles")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("PDG/gpt2_ft_police_articles")
    model = AutoModelForCausalLM.from_pretrained("PDG/gpt2_ft_police_articles")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use PDG/gpt2_ft_police_articles with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "PDG/gpt2_ft_police_articles"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "PDG/gpt2_ft_police_articles",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/PDG/gpt2_ft_police_articles
  • SGLang

    How to use PDG/gpt2_ft_police_articles 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 "PDG/gpt2_ft_police_articles" \
        --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": "PDG/gpt2_ft_police_articles",
    		"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 "PDG/gpt2_ft_police_articles" \
            --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": "PDG/gpt2_ft_police_articles",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use PDG/gpt2_ft_police_articles with Docker Model Runner:

    docker model run hf.co/PDG/gpt2_ft_police_articles
gpt2_ft_police_articles / runs
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  • 1 contributor
History: 34 commits
PDG's picture
PDG
Model save
139fa2d over 3 years ago
  • Feb01_09-25-49_1df9164d7de5
    Model save over 3 years ago
  • Feb01_11-20-08_1df9164d7de5
    Model save over 3 years ago
  • Feb01_14-13-29_1961cf1b1269
    Training in progress, epoch 1 over 3 years ago
  • Feb01_14-28-33_1961cf1b1269
    Training in progress, epoch 5 over 3 years ago
  • Feb07_21-49-53_e4adce1c568c
    Training in progress, epoch 1 over 3 years ago
  • Feb07_21-57-53_e4adce1c568c
    Training in progress, epoch 1 over 3 years ago
  • Feb07_22-02-06_e4adce1c568c
    Training in progress, epoch 1 over 3 years ago
  • Feb07_22-34-21_c6875808449e
    Training in progress, epoch 1 over 3 years ago
  • Feb07_22-59-43_d30ce19d15a8
    Model save over 3 years ago