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
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### Training Data
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### Training Procedure
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See detailed blog on preference tuning VLLMs [here](https://huggingface.co/blog/dpo_vlm).
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```bash
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accelerate launch --config_file examples/accelerate_configs/multi_gpu.yaml \
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### Training Data
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[HuggingFaceH4/rlaif-v_formatted](https://huggingface.co/datasets/HuggingFaceH4/rlaif-v_formatted)
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### Training Procedure
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See the detailed blog on preference tuning VLLMs [here](https://huggingface.co/blog/dpo_vlm).
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```bash
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accelerate launch --config_file examples/accelerate_configs/multi_gpu.yaml \
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