Instructions to use rithwik-db/sentiment_version_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rithwik-db/sentiment_version_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rithwik-db/sentiment_version_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rithwik-db/sentiment_version_4") model = AutoModelForSequenceClassification.from_pretrained("rithwik-db/sentiment_version_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5245e70e2e029e1059fb9f57c329b70d8327cd8715fb8fd5845421d51d4fe8d7
- Size of remote file:
- 268 MB
- SHA256:
- 372379096b322ebaaf3760f4d73d57b143fd9f88d19ea8311073fbb515e5240a
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