Instructions to use lentohaihane/r-4b-sft-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lentohaihane/r-4b-sft-code with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lentohaihane/r-4b-sft-code", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_r.RImageProcessor", | |
| "AutoProcessor": "processing_r.RProcessor" | |
| }, | |
| "do_convert_rgb": null, | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_grid_pinpoints": [ | |
| [ | |
| 384, | |
| 768 | |
| ], | |
| [ | |
| 768, | |
| 384 | |
| ], | |
| [ | |
| 768, | |
| 768 | |
| ], | |
| [ | |
| 1152, | |
| 384 | |
| ], | |
| [ | |
| 384, | |
| 1152 | |
| ] | |
| ], | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "RImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "RProcessor", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 384, | |
| "width": 384 | |
| } | |
| } | |