Instructions to use MMG/xlm-roberta-base-sa-spanish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMG/xlm-roberta-base-sa-spanish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MMG/xlm-roberta-base-sa-spanish")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MMG/xlm-roberta-base-sa-spanish") model = AutoModelForSequenceClassification.from_pretrained("MMG/xlm-roberta-base-sa-spanish") - Notebooks
- Google Colab
- Kaggle
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("MMG/xlm-roberta-base-sa-spanish")
model = AutoModelForSequenceClassification.from_pretrained("MMG/xlm-roberta-base-sa-spanish")
pipe = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
pipe(["Este bar es horrible", "Este bar es buenísimo"]))
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