Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use RonTon05/XMLRoberta_Dataset9kMeta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RonTon05/XMLRoberta_Dataset9kMeta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RonTon05/XMLRoberta_Dataset9kMeta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RonTon05/XMLRoberta_Dataset9kMeta") model = AutoModelForSequenceClassification.from_pretrained("RonTon05/XMLRoberta_Dataset9kMeta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74c2dfbe8c806364d8a726f308cdb086b1aa8bcdc280bf89e964c2796b7ed6d7
- Size of remote file:
- 17.1 MB
- SHA256:
- 252c24077824973279b663c6de6704d54e0ef405be31a583c1b304059a6bdbde
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