55 lines
2.1 KiB
Markdown
55 lines
2.1 KiB
Markdown
# Finetune SmolVLM2 with Axolotl
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[SmolVLM2](https://huggingface.co/collections/HuggingFaceTB/smolvlm2-smallest-video-lm-ever-67ab6b5e84bf8aaa60cb17c7) are a family of lightweight, open-source multimodal models from HuggingFace designed to analyze and understand video, image, and text content.
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These models are built for efficiency, making them well-suited for on-device applications where computational resources are limited. Models are available in multiple sizes, including 2.2B, 500M, and 256M.
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This guide shows how to fine-tune SmolVLM2 models with Axolotl.
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## Getting Started
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1. Install Axolotl following the [installation guide](https://docs.axolotl.ai/docs/installation.html).
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Here is an example of how to install from pip:
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```bash
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# Ensure you have a compatible version of Pytorch installed
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# Option A: manage dependencies in your project
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uv add 'axolotl>=0.12.0'
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uv pip install flash-attn --no-build-isolation
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# Option B: quick install
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uv pip install 'axolotl>=0.12.0'
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uv pip install flash-attn --no-build-isolation
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```
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2. Install an extra dependency:
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```bash
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uv pip install num2words==0.5.14
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```
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3. Run the finetuning example:
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```bash
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# LoRA SFT (1x48GB @ 6.8GiB)
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axolotl train examples/smolvlm2/smolvlm2-2B-lora.yaml
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```
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## TIPS
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- **Dataset Format**: For video finetuning, your dataset must be compatible with the multi-content Messages format. For more details, see our documentation on [Multimodal Formats](https://docs.axolotl.ai/docs/multimodal.html#dataset-format).
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- **Dataset Loading**: Read more on how to prepare and load your own datasets in our [documentation](https://docs.axolotl.ai/docs/dataset_loading.html).
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## Optimization Guides
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- [Multi-GPU Training](https://docs.axolotl.ai/docs/multi-gpu.html)
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- [LoRA Optimizations](https://docs.axolotl.ai/docs/lora_optims.html)
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- [Multi-Node Training](https://docs.axolotl.ai/docs/multi-node.html)
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## Related Resources
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- [SmolVLM2 Blog](https://huggingface.co/blog/smolvlm2)
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- [Axolotl Docs](https://docs.axolotl.ai)
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- [Axolotl GitHub](https://github.com/axolotl-ai-cloud/axolotl)
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- [Axolotl Discord](https://discord.gg/7m9sfhzaf3)
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