Instructions to use evelinamorim/token_classification_agreement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use evelinamorim/token_classification_agreement with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="evelinamorim/token_classification_agreement")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("evelinamorim/token_classification_agreement") model = AutoModelForTokenClassification.from_pretrained("evelinamorim/token_classification_agreement", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from evelinamorim/token_classification_agreement: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/evelinamorim/token_classification_agreement/resolve/main/training_args.bin
- Command line
-
hf download hf://evelinamorim/token_classification_agreement/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/evelinamorim/token_classification_agreement/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- ba778514a65c53c50c9e92a187db9fcc7bf37351bb95a3279307e4dcfd7442cb
- Size of remote file:
- 4.6 kB
- SHA256:
- 2c4e46e4f4fbebd3fb2c33dcf4536d5b3fc3c9edc7edfb041e1ee1f0568c181e
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