Instructions to use bertin-project/bertin-base-pos-conll2002-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-base-pos-conll2002-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bertin-project/bertin-base-pos-conll2002-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-pos-conll2002-es") model = AutoModelForTokenClassification.from_pretrained("bertin-project/bertin-base-pos-conll2002-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bertin-project/bertin-base-pos-conll2002-es: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/bertin-project/bertin-base-pos-conll2002-es/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bertin-project/bertin-base-pos-conll2002-es/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bertin-project/bertin-base-pos-conll2002-es/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- f294834fc43e6bde8d1e766872f0868e80c5d252dcc40039034f0154163a9a89
- Size of remote file:
- 496 MB
- SHA256:
- 804059e230f69819051c05748336cdcc1bf40e9ea3e52b36a907243fcd80b617
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