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wi-lab
/
lwm

Feature Extraction
Transformers
PyTorch
wireless-communication
few-shot-learning
limited-data
Model card Files Files and versions
xet
Community
7

Instructions to use wi-lab/lwm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use wi-lab/lwm with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="wi-lab/lwm")
    # Load model directly
    from transformers import LWM
    model = LWM.from_pretrained("wi-lab/lwm", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
lwm
27.3 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 217 commits
wi-lab's picture
wi-lab
Rename utils/beamforming.py to utils/robust_bf.py
3096624 verified about 1 year ago
  • utils
    Rename utils/beamforming.py to utils/robust_bf.py about 1 year ago
  • .gitattributes
    1.57 kB
    Upload lwm_paper.pdf over 1 year ago
  • .gitignore
    7 Bytes
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  • README.md
    19.7 kB
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  • config.json
    108 Bytes
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  • inference.py
    2.55 kB
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  • input_preprocess.py
    13.5 kB
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  • lwm_model.py
    5.03 kB
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  • lwm_paper.pdf
    24.7 MB
    xet
    Upload lwm_paper.pdf about 1 year ago
  • model_weights.pth

    Detected Pickle imports (3)

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

    What is a pickle import?

    2.51 MB
    xet
    upload required files over 1 year ago
  • tutorial.py
    11.6 kB
    Upload tutorial.py over 1 year ago
  • utils.py
    12.2 kB
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