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:
- 3293e053ab4288dfcd27a8a74ba062772321efe19b7d7231e505d13933719ed6
- Size of remote file:
- 5.2 kB
- SHA256:
- e7a40a9a474631d6086ebb283b9b06f646528a57bc15acdb03671c5356ac7902
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