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:
- a891d70d08f30b6511781aeac0ed857fedeb288044110dbe46329201413d08f8
- Size of remote file:
- 2.24 GB
- SHA256:
- be9fb2e013ab26255672a635b4e7d98d7c0c3ec63d947d9d8ae9e3521cf92b93
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