Instructions to use mag28/BLIPvizwiz2LoRA4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mag28/BLIPvizwiz2LoRA4 with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/blip-image-captioning-base") model = PeftModel.from_pretrained(base_model, "mag28/BLIPvizwiz2LoRA4") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from mag28/BLIPvizwiz2LoRA4: direct link, hf CLI and curl.
- Browser
- Download file 431 Bytes
-
https://huggingface.co/mag28/BLIPvizwiz2LoRA4/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://mag28/BLIPvizwiz2LoRA4/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/mag28/BLIPvizwiz2LoRA4/resolve/main/preprocessor_config.json
431 Bytes
| { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "BlipImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "processor_class": "BlipProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 384, | |
| "width": 384 | |
| } | |
| } | |