Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ludo33/e5_Eau_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ludo33/e5_Eau_v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ludo33/e5_Eau_v4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ludo33/e5_Eau_v4") model = AutoModelForSequenceClassification.from_pretrained("Ludo33/e5_Eau_v4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 681da5033b8bbfdfca3eeb489a94aa33e654ab3b79b7b842ef3fa7c669f6ebd8
- Size of remote file:
- 2.24 GB
- SHA256:
- 6c6422a3a14765c3cb75de30753235de878a14932def983be65a80c9f7691dd3
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