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:
- 6067dd1278ed25ac23c27a5f2a8dd956149d1174be83fd97353aba6b3c23e8a1
- Size of remote file:
- 3.58 kB
- SHA256:
- 0986c3cb5f58b4101df1fb25f0e37f65d2b9c2661d42b41757793ae41584ee04
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