Text Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
Sentiment Classification
Finance
Deberta-v2
text-embeddings-inference
Instructions to use RashidNLP/Finance-Sentiment-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RashidNLP/Finance-Sentiment-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RashidNLP/Finance-Sentiment-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RashidNLP/Finance-Sentiment-Classification") model = AutoModelForSequenceClassification.from_pretrained("RashidNLP/Finance-Sentiment-Classification") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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datasets:
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- financial_phrasebank
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- chiapudding/kaggle-financial-sentiment
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- zeroshot/twitter-financial-news-sentiment
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- FinanceInc/auditor_sentiment
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language:
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- en
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library_name: transformers
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tags:
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- Sentiment Classification
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- Finance
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- Deberta-v2
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