Instructions to use jxu124/TiO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jxu124/TiO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jxu124/TiO", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jxu124/TiO", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2a55a634511b42be540c00b95540b04e3a75d67b7e7bdf7cf36a06ddc80c1580
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size 4394150416
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