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:
- 2d20995536a24cba5f3bc42df733b9f15ba4c4a1f5e0276a1b1ca1b815602936
- Size of remote file:
- 5.18 kB
- SHA256:
- 9de90e8128a614c80eaf45fc87f39e1cfd219f122817be8e83f61f79da9b4947
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