Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use suhasy2/fin_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suhasy2/fin_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="suhasy2/fin_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("suhasy2/fin_sentiment") model = AutoModelForSequenceClassification.from_pretrained("suhasy2/fin_sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c4209c342237a16dfbcb37f2dfef28eb0b599e2b83b23d67ec50e2bf0dd9697
- Size of remote file:
- 268 MB
- SHA256:
- 6107267dc0de0c585c669772f4068eb3b2223294b85770ece1a59ccc4ca4038f
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