Instructions to use yangwang825/svector-aam-aug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangwang825/svector-aam-aug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="yangwang825/svector-aam-aug", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yangwang825/svector-aam-aug", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb55ce5bc95432261136e36f25a5e722a204cd81cf6ea6cce35b28dc8b2e72a6
- Size of remote file:
- 65.3 MB
- SHA256:
- ec8cb0eda406d6093ef29994b33f432b968471087b8be85ac4cc711c59ed2963
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