Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Hyeonseo/finance_news_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hyeonseo/finance_news_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hyeonseo/finance_news_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hyeonseo/finance_news_classifier") model = AutoModelForSequenceClassification.from_pretrained("Hyeonseo/finance_news_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71d5b747eba0ac394edd3fa6bfa2a605c8dc9bd705a09902b200c2ee7897cdc7
- Size of remote file:
- 1.11 GB
- SHA256:
- 1fa51958616e0e33ccbd3636ea6cd0c21be03935fb3594658129ece62a71b2c1
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