Instructions to use pabagcha/alc_robertuito with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pabagcha/alc_robertuito with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pabagcha/alc_robertuito")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/alc_robertuito") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/alc_robertuito") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5503d62b73edeb69ffa096c1abbb03a1eb60d42b883d878855f4642e27792a2
- Size of remote file:
- 439 MB
- SHA256:
- 968065c75b7c6fb292b54b86e4f5c0009ac8ae2c689c82f741e4ccfec2d1a81c
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