Text Classification
Transformers
Safetensors
English
deberta-v2
financial-sentiment
finance
sentiment-analysis
deberta-v3
Eval Results (legacy)
text-embeddings-inference
Instructions to use 9mark9/finbert-deberta-large-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 9mark9/finbert-deberta-large-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="9mark9/finbert-deberta-large-sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("9mark9/finbert-deberta-large-sentiment") model = AutoModelForSequenceClassification.from_pretrained("9mark9/finbert-deberta-large-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
8 days ago
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Document that the tweet accuracy depends on the transformers version (90.16 on 4.x, 89.53 on 5.x)
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Correct the tweet accuracy to the re-scored published weights (89.53%)
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9 days ago
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Note that the temporary training Space and checkpoint repos were removed
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Add DeBERTa-v3-large financial sentiment model, card, training and scoring scripts
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initial commit
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