Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use whyabhinay/fin_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whyabhinay/fin_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whyabhinay/fin_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whyabhinay/fin_sentiment") model = AutoModelForSequenceClassification.from_pretrained("whyabhinay/fin_sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4340315fdc38dc2280d4981b777bd96ca8fb516b6f9c2d5cd2f8f6f4d075899
- Size of remote file:
- 3.44 kB
- SHA256:
- 09f8ef5d92e76a2f8d9c9b3bee7460e5775d31bab1d4a28de9b977b50e566517
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