Text Classification
Transformers
PyTorch
Safetensors
French
camembert
financial-sentiment-analysis
sentiment-analysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/finance-sentiment-fr-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-fr-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-fr-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-fr-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-fr-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e48d5cd1dab14a1f1f0c7c83be6a840774f512f9d1afbf6b6565683ffb1568e
- Size of remote file:
- 443 MB
- SHA256:
- 29712a7482d75878fc6b671010b82ebcbccbf50fcb0a7f830fb76f5eeebf7b27
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