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n0w0f
/
MatText-atom-seq-plusplus-2m

Feature Extraction
Transformers
Safetensors
English
bert
chemistry
materials
pretrained
Model card Files Files and versions
xet
Community

Instructions to use n0w0f/MatText-atom-seq-plusplus-2m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use n0w0f/MatText-atom-seq-plusplus-2m with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="n0w0f/MatText-atom-seq-plusplus-2m")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("n0w0f/MatText-atom-seq-plusplus-2m")
    model = AutoModel.from_pretrained("n0w0f/MatText-atom-seq-plusplus-2m")
  • Notebooks
  • Google Colab
  • Kaggle
MatText-atom-seq-plusplus-2m
131 MB
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  • 1 contributor
History: 5 commits
n0w0f's picture
n0w0f
add citation block
19d22df verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    4.26 kB
    add citation block almost 2 years ago
  • config.json
    731 Bytes
    Upload model almost 2 years ago
  • model.safetensors
    131 MB
    xet
    Upload model almost 2 years ago