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EnDevSols
/
falcon-7b

Text Generation
Transformers
PyTorch
English
RefinedWebModel
custom_code
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use EnDevSols/falcon-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use EnDevSols/falcon-7b with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="EnDevSols/falcon-7b", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("EnDevSols/falcon-7b", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use EnDevSols/falcon-7b with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "EnDevSols/falcon-7b"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "EnDevSols/falcon-7b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/EnDevSols/falcon-7b
  • SGLang

    How to use EnDevSols/falcon-7b 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 "EnDevSols/falcon-7b" \
        --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": "EnDevSols/falcon-7b",
    		"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 "EnDevSols/falcon-7b" \
            --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": "EnDevSols/falcon-7b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use EnDevSols/falcon-7b with Docker Model Runner:

    docker model run hf.co/EnDevSols/falcon-7b
falcon-7b
13.6 GB
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  • 1 contributor
History: 10 commits
muzammil-eds's picture
muzammil-eds
Update README.md
11feb53 almost 3 years ago
  • .gitattributes
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    initial commit almost 3 years ago
  • README.md
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  • config.json
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  • configuration_RW.py
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  • generation_config.json
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  • handler.py
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    Create handler.py almost 3 years ago
  • modelling_RW.py
    47.6 kB
    Create modelling_RW.py almost 3 years ago
  • pytorch_model-00001-of-00002.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    9.96 GB
    xet
    Upload RWForCausalLM almost 3 years ago
  • pytorch_model-00002-of-00002.bin

    Detected Pickle imports (5)

    • "torch.FloatStorage",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_meta_tensor_no_storage",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.float32"

    How to fix it?

    3.64 GB
    xet
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  • pytorch_model.bin.index.json
    16.9 kB
    Upload RWForCausalLM almost 3 years ago
  • requirements.txt
    102 Bytes
    Create requirements.txt almost 3 years ago
  • special_tokens_map.json
    313 Bytes
    Upload tokenizer almost 3 years ago
  • tokenizer.json
    2.73 MB
    Upload tokenizer almost 3 years ago
  • tokenizer_config.json
    180 Bytes
    Upload tokenizer almost 3 years ago