Instructions to use AIDA-UPM/star with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIDA-UPM/star with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AIDA-UPM/star")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AIDA-UPM/star") model = AutoModel.from_pretrained("AIDA-UPM/star") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
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- model.safetensors +3 -0
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model.safetensors filter=lfs diff=lfs merge=lfs -text
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version https://git-lfs.github.com/spec/v1
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oid sha256:93d79fcf6ab0530388e79d29c21a7ba82c3e07d9ed7266efcabec3cd85169fab
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size 1421488104
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