Instructions to use pysentimiento/robertuito-pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pysentimiento/robertuito-pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pysentimiento/robertuito-pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pysentimiento/robertuito-pos") model = AutoModelForTokenClassification.from_pretrained("pysentimiento/robertuito-pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pysentimiento/robertuito-pos: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/pysentimiento/robertuito-pos/resolve/main/training_args.bin
- Command line
-
hf download hf://pysentimiento/robertuito-pos/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pysentimiento/robertuito-pos/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 0a76e358898f2d471f0a7b79062f0dd98e55fc2b8f85d0e1c3b537f4c41ff53e
- Size of remote file:
- 2.86 kB
- SHA256:
- b31f0f88eb6af616c32b715486d1c414cf8d63bab2b0deb3da954b854a6c6cc7
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