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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd3c948d8b7d2523ba21e4e8ca8969fbf9948ccd12254e9d6d69ead93d6f2821
- Size of remote file:
- 3.58 kB
- SHA256:
- ff8246041980f6c647203aa509baa4241616153d6c74cd39ad70d5ce7bb9ad22
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