Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ludo33/e5_General_2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ludo33/e5_General_2026 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ludo33/e5_General_2026")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ludo33/e5_General_2026") model = AutoModelForSequenceClassification.from_pretrained("Ludo33/e5_General_2026", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efe99592a5bd518205f1d1dae9dc7b244882b190f87ce781406d008f8a5281d7
- Size of remote file:
- 17.1 MB
- SHA256:
- e63c7a5faf7f3257542d756311f64572a52913c2845c4a3849529e1ef87f8eef
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