Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ludo33/e5_General_2026_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ludo33/e5_General_2026_V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ludo33/e5_General_2026_V2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ludo33/e5_General_2026_V2") model = AutoModelForSequenceClassification.from_pretrained("Ludo33/e5_General_2026_V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef1192ea2ab9902205b50ea54e3a0bb6453cc3da7b3926f857bfd588cdb480f2
- Size of remote file:
- 5.2 kB
- SHA256:
- d1b66d7991ef0844753a23749528ed9c48fd46eff05aab014b1884295ab6bb60
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.