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Instructions to use ProCogia/Euclid-2.6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCogia/Euclid-2.6 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-2.6")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ProCogia/Euclid-2.6") model = AutoModelForMultimodalLM.from_pretrained("ProCogia/Euclid-2.6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "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 | |
| } | |