Instructions to use AnonymousSub/AR_consert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/AR_consert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AnonymousSub/AR_consert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/AR_consert") model = AutoModel.from_pretrained("AnonymousSub/AR_consert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a29184ab097a32e643b6b5a8b4dc94a34cdd5c11563a259ea8d49f474dd50e7
- Size of remote file:
- 438 MB
- SHA256:
- c5fbc055c5d7f3201b5114fd29d97b5a952b64414a4ea2411919a060ee6846eb
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