Instructions to use somusan/molmo2-vqa-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use somusan/molmo2-vqa-lora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("somusan/molmo2-vqa-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download final_adapter/processor_config.json from somusan/molmo2-vqa-lora: direct link, hf CLI and curl.
- Browser
- Download file 301 Bytes
-
https://huggingface.co/somusan/molmo2-vqa-lora/resolve/main/final_adapter/processor_config.json
- Command line
-
hf download hf://somusan/molmo2-vqa-lora/final_adapter/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/somusan/molmo2-vqa-lora/resolve/main/final_adapter/processor_config.json
301 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_molmo2.Molmo2Processor" | |
| }, | |
| "image_use_col_tokens": true, | |
| "processor_class": "Molmo2Processor", | |
| "use_frame_special_tokens": false, | |
| "use_single_crop_col_tokens": false, | |
| "use_single_crop_start_token": true, | |
| "video_use_col_tokens": false | |
| } | |