Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ludo33/e5_Energie_MultiLabel_12082025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ludo33/e5_Energie_MultiLabel_12082025 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ludo33/e5_Energie_MultiLabel_12082025")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ludo33/e5_Energie_MultiLabel_12082025") model = AutoModelForSequenceClassification.from_pretrained("Ludo33/e5_Energie_MultiLabel_12082025") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7dc63ec6821d71cfcfa50a9e040e5c85cbb017cdb7cc4bee1a7a1cbec8961e9e
- Size of remote file:
- 5.43 kB
- SHA256:
- 709db0840c90704713b47db52330600b6cf09bd9a7bfaf52d040907044cc8d1a
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