Instructions to use bertugmirasyedi/deberta-v3-base-level-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertugmirasyedi/deberta-v3-base-level-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bertugmirasyedi/deberta-v3-base-level-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bertugmirasyedi/deberta-v3-base-level-classification") model = AutoModelForSequenceClassification.from_pretrained("bertugmirasyedi/deberta-v3-base-level-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from bertugmirasyedi/deberta-v3-base-level-classification: direct link, hf CLI and curl.
- Browser
- Download file 23 Bytes
-
https://huggingface.co/bertugmirasyedi/deberta-v3-base-level-classification/resolve/main/added_tokens.json
- Command line
-
hf download hf://bertugmirasyedi/deberta-v3-base-level-classification/added_tokens.json
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curl -L -o added_tokens.json https://huggingface.co/bertugmirasyedi/deberta-v3-base-level-classification/resolve/main/added_tokens.json
23 Bytes
| { | |
| "[MASK]": 128000 | |
| } | |