Instructions to use nrizwan/fhm-label-internvl-model-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nrizwan/fhm-label-internvl-model-all with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nrizwan/fhm-label-internvl-model-all", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,271 Bytes
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"image_processor": {
"crop_to_patches": false,
"data_format": "channels_first",
"default_to_square": true,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "GotOcr2ImageProcessorFast",
"image_std": [
0.229,
0.224,
0.225
],
"max_patches": 12,
"min_patches": 1,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 448,
"width": 448
}
},
"image_seq_length": 256,
"processor_class": "InternVLProcessor",
"video_processor": {
"data_format": "channels_first",
"default_to_square": true,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"do_sample_frames": false,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"initial_shift": true,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"return_metadata": false,
"size": {
"height": 384,
"width": 384
},
"video_processor_type": "InternVLVideoProcessor"
}
}
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