Instructions to use saracandu/stldec_arch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saracandu/stldec_arch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="saracandu/stldec_arch", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("saracandu/stldec_arch", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1f3c3c5dd01b3a55f04ceabb5f778b164fed2887f5b009cc4ea575c8d314f60
- Size of remote file:
- 806 MB
- SHA256:
- 3f157441cbfe4dfac077d246a46ff036a3a65ea89bb44d9f911626353a4319cb
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