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:
- 2beecfc2009a57967e086f74fdb3d730316481a9dc6e1e60a9c13fa78a812db0
- Size of remote file:
- 5.84 kB
- SHA256:
- 46e390ff09e3a52214848d7d479a9518f6c00c1e7d781a0d95e9537cac2f6b70
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