Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use davanstrien/demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/demo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/demo") model = AutoModelForSequenceClassification.from_pretrained("davanstrien/demo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31cfad7e457e392bdebe2bd63796205ff3f6ab825e13da0a03d83dfbf932c919
- Size of remote file:
- 17.1 MB
- SHA256:
- 62c24cdc13d4c9952d63718d6c9fa4c287974249e16b7ade6d5a85e7bbb75626
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