Instructions to use AnonymousSub/SR_consert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/SR_consert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AnonymousSub/SR_consert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/SR_consert") model = AutoModel.from_pretrained("AnonymousSub/SR_consert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 891280094bf41e17823dfd534f7e4bb87737b340c7d39f52a71926f97631f661
- Size of remote file:
- 438 MB
- SHA256:
- 2b7e31ea682fa63973e27588fdfc8ade45a2b78025bec55b9233f0024cf029ac
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