Image Feature Extraction
Transformers
Safetensors
pixtral_large4_vision
feature-extraction
vision
custom_code
Instructions to use immanuelpeter/PixtralViT-Large-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use immanuelpeter/PixtralViT-Large-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="immanuelpeter/PixtralViT-Large-4", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("immanuelpeter/PixtralViT-Large-4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 466 Bytes
204c1fe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"do_convert_rgb": true,
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_processor_type": "PixtralImageProcessor",
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"patch_size": 14,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"longest_edge": 1540
},
"processor_class": "AutoImageProcessor"
}
|