Text Classification
Transformers
Safetensors
multilingual
deberta-v2
custom_code
text-embeddings-inference
Instructions to use utter-project/EuroFilter-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utter-project/EuroFilter-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="utter-project/EuroFilter-v1", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("utter-project/EuroFilter-v1", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("utter-project/EuroFilter-v1", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93be75d241c281f0ab4339138b127b60b7d0ad42510a999c6bab10c0cfb5b52b
- Size of remote file:
- 16.4 MB
- SHA256:
- d5249d92f8d658ed3d19f52a5885b7abbf7f82a90cc18a2b6c7166af54a884f6
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