Instructions to use AnonymousSub/SR_specter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/SR_specter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AnonymousSub/SR_specter")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/SR_specter") model = AutoModel.from_pretrained("AnonymousSub/SR_specter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7fe91cf0b0f81989d499ce9d62053e03a596ae5ddcbf046a180cb2aae6d67001
- Size of remote file:
- 438 MB
- SHA256:
- 11782d0a940550f1169481a3689f372347dc3fe10c57a2744de73cd6f800b713
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