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Alverciito
/
beast_cased

Feature Extraction
Transformers
Safetensors
Spanish
beast
embeddings
static-embeddings
byte-level
tokenizer-free
spanish
small-language-models
knowledge-distillation
custom_code
Model card Files Files and versions
xet
Community

Instructions to use Alverciito/beast_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Alverciito/beast_cased with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Alverciito/beast_cased", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Alverciito/beast_cased", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
beast_cased
1.09 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
Chiquitin
Merge remote-tracking branch 'origin/main'
6888605 5 months ago
  • research_files
    upload pairplot and requirements.txt 5 months ago
  • .gitattributes
    1.67 kB
    Initial clean commit (no binary history) 5 months ago
  • README.md
    4.99 kB
    Update README.md 5 months ago
  • beast_tokenizer.py
    3.64 kB
    Initial clean commit (no binary history) 5 months ago
  • config.json
    311 Bytes
    Initial clean commit (no binary history) 5 months ago
  • model.safetensors
    25.5 MB
    xet
    Initial clean commit (no binary history) 5 months ago
  • modeling.py
    13 kB
    Initial clean commit (no binary history) 5 months ago
  • requirements.txt
    263 Bytes
    upload pairplot and requirements.txt 5 months ago
  • tokenizer_config.json
    193 Bytes
    Initial clean commit (no binary history) 5 months ago