Instructions to use HaochenWang/GAR-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HaochenWang/GAR-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="HaochenWang/GAR-8B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HaochenWang/GAR-8B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 909 Bytes
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"auto_map": {
"AutoImageProcessor": "image_processing_perception_lm_fast.PerceptionLMImageProcessorFast",
"AutoProcessor": "processing_gar.GARPerceptionLMProcessor"
},
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"data_format": "channels_first",
"default_to_square": true,
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"do_center_crop": false,
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"do_resize": true,
"image_mean": [
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"image_processor_type": "PerceptionLMImageProcessorFast",
"image_std": [
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"processor_class": "GARPerceptionLMProcessor",
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"return_tensors": null,
"size": {
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}
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