Instructions to use HiTZ/mbert-argmining-abstrct-en-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/mbert-argmining-abstrct-en-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HiTZ/mbert-argmining-abstrct-en-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HiTZ/mbert-argmining-abstrct-en-es") model = AutoModelForTokenClassification.from_pretrained("HiTZ/mbert-argmining-abstrct-en-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from HiTZ/mbert-argmining-abstrct-en-es: direct link, hf CLI and curl.
- Browser
- Download file 2.92 MB
-
https://huggingface.co/HiTZ/mbert-argmining-abstrct-en-es/resolve/main/tokenizer.json
- Command line
-
hf download hf://HiTZ/mbert-argmining-abstrct-en-es/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/HiTZ/mbert-argmining-abstrct-en-es/resolve/main/tokenizer.json
2.92 MB
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