Instructions to use MoTHer-VTHR/VTHR-LoRA-F-ModelTree_2-Depth_0-Node_zA4aeZqL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoTHer-VTHR/VTHR-LoRA-F-ModelTree_2-Depth_0-Node_zA4aeZqL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="MoTHer-VTHR/VTHR-LoRA-F-ModelTree_2-Depth_0-Node_zA4aeZqL")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("MoTHer-VTHR/VTHR-LoRA-F-ModelTree_2-Depth_0-Node_zA4aeZqL") model = AutoModel.from_pretrained("MoTHer-VTHR/VTHR-LoRA-F-ModelTree_2-Depth_0-Node_zA4aeZqL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
config.json
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"patch_size": 16,
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.40.
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}
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"patch_size": 16,
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.40.1"
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}
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