Instructions to use hf-internal-testing/tiny-random-groupvit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-groupvit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-groupvit")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-groupvit") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-groupvit") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +2 -2
- pytorch_model.bin +2 -2
config.json
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"logit_scale_init_value": 2.6592,
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"model_type": "groupvit",
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"output_segmentation": false,
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"projection_dim":
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"projection_intermediate_dim":
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"text_config": {
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"_name_or_path": "",
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"add_cross_attention": false,
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"logit_scale_init_value": 2.6592,
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"model_type": "groupvit",
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"output_segmentation": false,
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"projection_dim": 256,
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"projection_intermediate_dim": 4096,
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"text_config": {
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"_name_or_path": "",
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"add_cross_attention": false,
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 12058931
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