Feature Extraction
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ludo33/e5_Eau_Multilabel_Topic_Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ludo33/e5_Eau_Multilabel_Topic_Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Ludo33/e5_Eau_Multilabel_Topic_Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Ludo33/e5_Eau_Multilabel_Topic_Sentiment") model = AutoModel.from_pretrained("Ludo33/e5_Eau_Multilabel_Topic_Sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a558cbf2b1ab9a580059a05aaac3d8312cbce77e622a04e2343426bb66b3c41f
- Size of remote file:
- 42.5 kB
- SHA256:
- 9896e7da8d92342b8a48047fc19e51a7dc359a7a2b623086a26c4cb20f694e0b
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