Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
financial-sentiment-analysis
sentiment-analysis
sentence_50agree
stocks
sentiment
finance
text-embeddings-inference
Instructions to use nickmuchi/deberta-v3-base-finetuned-finance-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickmuchi/deberta-v3-base-finetuned-finance-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nickmuchi/deberta-v3-base-finetuned-finance-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nickmuchi/deberta-v3-base-finetuned-finance-text-classification") model = AutoModelForSequenceClassification.from_pretrained("nickmuchi/deberta-v3-base-finetuned-finance-text-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3747c7a823bcf57e34246eb27af80bf12d869f306da5e5d7a27a73e7865205b3
- Size of remote file:
- 3.31 kB
- SHA256:
- 884d1f0a1fb9c763a239abdf32a0d2b260dc0989d65533eb5842d6656aa84901
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