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)# pip install -U transformers accelerate # 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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from utter-project/EuroFilter-v1: direct link, hf CLI and curl.
- Browser
- Download file 286 Bytes
-
https://huggingface.co/utter-project/EuroFilter-v1/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://utter-project/EuroFilter-v1/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/utter-project/EuroFilter-v1/resolve/main/special_tokens_map.json
286 Bytes
| { | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |