Instructions to use Tommidi/st_vit_pretrained-1epoch-ucf101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tommidi/st_vit_pretrained-1epoch-ucf101 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import ST_Vit model = ST_Vit.from_pretrained("Tommidi/st_vit_pretrained-1epoch-ucf101", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +20 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
config.json
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{
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"_name_or_path": "Tommidi/st_vit_untrained-101",
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"architectures": [
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"ST_Vit"
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],
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"model_type": "st_vit",
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"out_channels": 101,
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"spatial_vit": {
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"model_type": "vit"
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},
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"temporal_vit": {
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"model_type": "vit"
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},
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"temporal_vit_mae": {
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"model_type": "vit_mae",
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"out_channels": 101
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},
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"torch_dtype": "float32",
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"transformers_version": "4.40.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1caf25f42260f5bb33831e813e39bb844e36859eecdd0a1a847d5a0a62f01f1d
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size 689126696
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:11d8935aa4f9bd227544f165ec40a57d70459df4324147da6ce8edc927017fb0
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size 5048
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