Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ludo33/e5_Eau_MultiLabel_Simple_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ludo33/e5_Eau_MultiLabel_Simple_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ludo33/e5_Eau_MultiLabel_Simple_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ludo33/e5_Eau_MultiLabel_Simple_v2") model = AutoModelForSequenceClassification.from_pretrained("Ludo33/e5_Eau_MultiLabel_Simple_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8451bd93da6a6ca3bf8e31ac060b753d93a445df1825ab61f69bd8d99f3d0ee3
- Size of remote file:
- 2.24 GB
- SHA256:
- 31c0c9d4c25cd6e192d73b1feb2f3414f58718f709f5a24bf8b4f61db6657abe
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