Instructions to use finiteautomata/beto-headlines-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use finiteautomata/beto-headlines-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="finiteautomata/beto-headlines-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("finiteautomata/beto-headlines-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("finiteautomata/beto-headlines-sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7aa1401ce408180248365241f5f5ddd63dabc9664cd735626e9842443b7f3e8
- Size of remote file:
- 439 MB
- SHA256:
- 19b08bcc6513eb5668281c4acbe4351426ddb4c1362e30722b9eb0e27557f2da
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