Instructions to use albertlp/model_deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertlp/model_deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="albertlp/model_deberta")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("albertlp/model_deberta") model = AutoModel.from_pretrained("albertlp/model_deberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3f88a92776e2aca297da1a39ecbb02041605b66f316b1ae7b860643d2f4ed9a
- Size of remote file:
- 735 MB
- SHA256:
- dabc32b6c63e163045fccd5cca3a6eece11d5ba898f2d9b1d7b2b4d2082d0a05
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