Instructions to use HuggingFaceTB/SmolVLM-Instruct-DPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HuggingFaceTB/SmolVLM-Instruct-DPO with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolVLM-Instruct") model = PeftModel.from_pretrained(base_model, "HuggingFaceTB/SmolVLM-Instruct-DPO") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_convert_rgb": true, | |
| "do_image_splitting": false, | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Idefics3ImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "max_image_size": { | |
| "longest_edge": 384 | |
| }, | |
| "processor_class": "Idefics3Processor", | |
| "resample": 1, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 1536 | |
| } | |
| } | |