Token Classification
spaCy
Spanish
named-entity-recognition
spanish
music
digital-humanities
historical-text
bert
Eval Results (legacy)
Instructions to use LexiMusUSAL/LexiMus-BETO-per-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use LexiMusUSAL/LexiMus-BETO-per-v1 with spaCy:
!pip install https://huggingface.co/LexiMusUSAL/LexiMus-BETO-per-v1/resolve/main/LexiMus-BETO-per-v1-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("LexiMus-BETO-per-v1") # Importing as module. import LexiMus-BETO-per-v1 nlp = LexiMus-BETO-per-v1.load() - Notebooks
- Google Colab
- Kaggle
Subida inicial LexiMus-BETO-per-v1 [8/25]
Browse files
lemmatizer/lookups/lookups.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:ee3740fdad2ebc1cf79a63a8e5b2d2f3dd47b33c3a7a0bc9351ba5a1246b6a07
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size 165225
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