Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use rithwik-db/sentiment_version_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rithwik-db/sentiment_version_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rithwik-db/sentiment_version_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rithwik-db/sentiment_version_2") model = AutoModelForSequenceClassification.from_pretrained("rithwik-db/sentiment_version_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01579e18f1487c25fac49061fcdeddb83cc2e86ae57c77cd9305a69d788e4d4f
- Size of remote file:
- 3.58 kB
- SHA256:
- f79d963bde7610f1728557e1c5754f819edfb4382b6fa6e5db754e9c8af6741b
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