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Instructions to use ProCogia/Euclid-2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCogia/Euclid-2.5 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="ProCogia/Euclid-2.5")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ProCogia/Euclid-2.5") model = AutoModelForMultimodalLM.from_pretrained("ProCogia/Euclid-2.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 976 Bytes
07accfa | 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 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | {
"image_break_token": "[IMG_BREAK]",
"image_end_token": "[IMG_END]",
"image_processor": {
"crop_size": null,
"data_format": "channels_first",
"device": null,
"disable_grouping": null,
"do_center_crop": null,
"do_convert_rgb": true,
"do_normalize": true,
"do_pad": null,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_processor_type": "PixtralImageProcessorFast",
"image_seq_length": null,
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"input_data_format": null,
"pad_size": null,
"patch_size": 14,
"processor_class": "PixtralProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"return_tensors": null,
"size": {
"longest_edge": 1540
}
},
"image_token": "[IMG]",
"patch_size": 14,
"processor_class": "PixtralProcessor",
"spatial_merge_size": 2
}
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