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
Download processor_config.json from HuggingFaceTB/SmolVLM-Instruct-DPO: direct link, hf CLI and curl.
- Browser
- Download file 68 Bytes
-
https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct-DPO/resolve/main/processor_config.json
- Command line
-
hf download hf://HuggingFaceTB/SmolVLM-Instruct-DPO/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct-DPO/resolve/main/processor_config.json
68 Bytes
| { | |
| "image_seq_len": 81, | |
| "processor_class": "Idefics3Processor" | |
| } | |