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ICB-UMA
/
HERBERT-P

Feature Extraction
Transformers
Safetensors
Spanish
roberta
contrastive-learning
Spanish-UMLS
Hierarchical-enrichment
entity-linking
biomedical
spanish
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ICB-UMA/HERBERT-P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ICB-UMA/HERBERT-P with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ICB-UMA/HERBERT-P")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ICB-UMA/HERBERT-P")
    model = AutoModel.from_pretrained("ICB-UMA/HERBERT-P")
  • Notebooks
  • Google Colab
  • Kaggle
HERBERT-P
509 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
fernandogd97's picture
fernandogd97
Update README.md
a14333e verified 11 months ago
  • .gitattributes
    1.52 kB
    initial commit 11 months ago
  • README.md
    1.28 kB
    Update README.md 11 months ago
  • config.json
    764 Bytes
    Upload model 11 months ago
  • merges.txt
    540 kB
    Upload tokenizer 11 months ago
  • model.safetensors
    504 MB
    xet
    Upload model 11 months ago
  • special_tokens_map.json
    957 Bytes
    Upload tokenizer 11 months ago
  • tokenizer.json
    3.82 MB
    Upload tokenizer 11 months ago
  • tokenizer_config.json
    1.29 kB
    Upload tokenizer 11 months ago
  • vocab.json
    894 kB
    Upload tokenizer 11 months ago