Instructions to use feserrm/clasificador-tweets2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use feserrm/clasificador-tweets2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="feserrm/clasificador-tweets2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("feserrm/clasificador-tweets2") model = AutoModelForSequenceClassification.from_pretrained("feserrm/clasificador-tweets2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a16af6aac54d4297e24596d3fbc9c109ed1aaf30581a168f5d379353c979e8d
- Size of remote file:
- 5.3 kB
- SHA256:
- efb3589d43deb494e3e8a8bf282e44f3b27a55117aa94da857f3f2531eb5fa77
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