Instructions to use Everlyn/sentiment_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Everlyn/sentiment_model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Everlyn/sentiment_model2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Everlyn/sentiment_model2") model = AutoModelForSequenceClassification.from_pretrained("Everlyn/sentiment_model2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6379a40d16d63c03e47b1eaaf7c2fd539fe089f7aea9b0cf4d3eccff6060f41
- Size of remote file:
- 499 MB
- SHA256:
- 1e06d907bdbe1abb75e4b11c067f71450c7f0ac44c74534f3d81e5393ecfc90e
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