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
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:765c0ca995e07ec453728939e41191ea4c65444737ad14b20a0d84b701fc9f8f
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size 737726548
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