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claritylab
/
zero-shot-implicit-gpt2

Text Generation
PyTorch
Transformers
sentence-transformers
English
zeroshot_classifier
gpt2
text-generation-inference
Model card Files Files and versions
xet
Community
1

Instructions to use claritylab/zero-shot-implicit-gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use claritylab/zero-shot-implicit-gpt2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="claritylab/zero-shot-implicit-gpt2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelWithLMHead
    
    tokenizer = AutoTokenizer.from_pretrained("claritylab/zero-shot-implicit-gpt2")
    model = AutoModelWithLMHead.from_pretrained("claritylab/zero-shot-implicit-gpt2")
  • sentence-transformers

    How to use claritylab/zero-shot-implicit-gpt2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("claritylab/zero-shot-implicit-gpt2")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use claritylab/zero-shot-implicit-gpt2 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "claritylab/zero-shot-implicit-gpt2"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "claritylab/zero-shot-implicit-gpt2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/claritylab/zero-shot-implicit-gpt2
  • SGLang

    How to use claritylab/zero-shot-implicit-gpt2 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 "claritylab/zero-shot-implicit-gpt2" \
        --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": "claritylab/zero-shot-implicit-gpt2",
    		"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 "claritylab/zero-shot-implicit-gpt2" \
            --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": "claritylab/zero-shot-implicit-gpt2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use claritylab/zero-shot-implicit-gpt2 with Docker Model Runner:

    docker model run hf.co/claritylab/zero-shot-implicit-gpt2
zero-shot-implicit-gpt2
1.45 GB
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  • 1 contributor
History: 6 commits
StefanH's picture
StefanH
Update README.md
f574d69 almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • README.md
    2.48 kB
    Update README.md almost 3 years ago
  • added_tokens.json
    194 Bytes
    add tokenizer almost 3 years ago
  • config.json
    1.11 kB
    add model almost 3 years ago
  • merges.txt
    456 kB
    add tokenizer almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch.ByteStorage",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    1.45 GB
    xet
    add model almost 3 years ago
  • special_tokens_map.json
    258 Bytes
    add tokenizer almost 3 years ago
  • tokenizer.json
    2.11 MB
    add tokenizer almost 3 years ago
  • tokenizer_config.json
    408 Bytes
    add tokenizer almost 3 years ago
  • vocab.json
    798 kB
    add tokenizer almost 3 years ago