Instructions to use AnonymousSub/SR_bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/SR_bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AnonymousSub/SR_bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/SR_bert-base-uncased") model = AutoModel.from_pretrained("AnonymousSub/SR_bert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a3c169a41d536eae9dcea56f295678dfa84ccf7cdcb42bc1270f14408c5a555
- Size of remote file:
- 438 MB
- SHA256:
- 702439632d88d9189bb121cef43c9b8703d2f682be0bdad7805f50210672f5c6
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