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crab27
/
llama3-edge

Feature Extraction
Transformers
Safetensors
PyTorch
llama_edge
custom-implementation
graph-prediction
edge-prediction
custom_code
Model card Files Files and versions
xet
Community

Instructions to use crab27/llama3-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use crab27/llama3-edge with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="crab27/llama3-edge", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("crab27/llama3-edge", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
llama3-edge
28.2 GB
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  • 1 contributor
History: 4 commits
crab27's picture
crab27
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3489e83 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    1.71 kB
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  • config.json
    529 Bytes
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  • configuration_llama_edge.py
    1.02 kB
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  • id_mapper.py
    2.63 kB
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  • inference.py
    4.63 kB
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  • model-00001-of-00006.safetensors
    4.93 GB
    xet
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  • model-00002-of-00006.safetensors
    5 GB
    xet
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  • model-00003-of-00006.safetensors
    4.83 GB
    xet
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  • model-00004-of-00006.safetensors
    5 GB
    xet
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  • model-00005-of-00006.safetensors
    5 GB
    xet
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  • model-00006-of-00006.safetensors
    3.48 GB
    xet
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  • model.safetensors.index.json
    21.4 kB
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  • modeling_llama_edge.py
    5.85 kB
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  • unified_id_mapper.json
    647 kB
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