Text Classification
Transformers
PyTorch
Safetensors
English
perceiver
financial-sentiment-analysis
sentiment-analysis
language-perceiver
Eval Results (legacy)
Instructions to use warwickai/fin-perceiver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use warwickai/fin-perceiver with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="warwickai/fin-perceiver")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("warwickai/fin-perceiver") model = AutoModelForSequenceClassification.from_pretrained("warwickai/fin-perceiver") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79335f4363122da2ef62807da427f665b94ae064165e5aebf988424b0bd6a3d7
- Size of remote file:
- 825 MB
- SHA256:
- a215a79a89c02c5821329e584c6de405e44dda87d1ebd7e4923fc46f927cf878
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