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FartLabs
/
FART_ChemBERTa-77M-MLM_W

Text Classification
Transformers
Safetensors
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use FartLabs/FART_ChemBERTa-77M-MLM_W with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use FartLabs/FART_ChemBERTa-77M-MLM_W with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="FartLabs/FART_ChemBERTa-77M-MLM_W")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("FartLabs/FART_ChemBERTa-77M-MLM_W")
    model = AutoModelForSequenceClassification.from_pretrained("FartLabs/FART_ChemBERTa-77M-MLM_W")
  • Notebooks
  • Google Colab
  • Kaggle
FART_ChemBERTa-77M-MLM_W
13.8 MB
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  • 1 contributor
History: 3 commits

This model has 1 file scanned as unsafe.

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ppestlin
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55ef93c verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    5.17 kB
    Upload RobertaForSequenceClassification almost 2 years ago
  • added_tokens.json
    32 Bytes
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  • config.json
    983 Bytes
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  • merges.txt
    14 Bytes
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  • model.safetensors
    13.7 MB
    xet
    Upload RobertaForSequenceClassification almost 2 years ago
  • special_tokens_map.json
    965 Bytes
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  • tokenizer.json
    14 kB
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  • tokenizer_config.json
    1.61 kB
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  • vocab.json
    6.96 kB
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