Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use will702/stockbit-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use will702/stockbit-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="will702/stockbit-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("will702/stockbit-sentiment") model = AutoModelForSequenceClassification.from_pretrained("will702/stockbit-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 971711a02923d180eb42b00871c715c2a40c48ecace5e152b16faf9e68ac72db
- Size of remote file:
- 2.73 MB
- SHA256:
- 81db0ac7ee0e79cfa444f320d6e77a85f345c66e4aec97b92b31da1db46958ca
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