418933f0d1
* feat: add internvl3_5 * fix: add timm instructions * chore: add kimi-linear to cce doc * feat: update internvl example * chore: pin revision * chore: remove from multipack * fix: add to multimodal array * fix: internvl use hf version * feat: update cce * chore: lint * fix: list for image_size * chore: add docs vram usage * feat: enable cce * fix: no need trust remote code * fix: inconsistent timm version
44 lines
1.7 KiB
Markdown
44 lines
1.7 KiB
Markdown
# Finetune OpenGV's InternVL with Axolotl
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[InternVL 3.5](https://huggingface.co/OpenGVLab/InternVL3_5-8B-HF) is a family of powerful vision-language models supporting dynamic resolution and multi-image understanding by OpenGV. It features a ViT-style vision encoder and strong language model backbone for tasks like visual question answering, OCR, and scene text understanding.
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This guide shows how to fine-tune it 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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2. Install `timm` for vision model support:
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```bash
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pip install timm==1.0.19
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```
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3. Install [Cut Cross Entropy](https://docs.axolotl.ai/docs/custom_integrations.html#cut-cross-entropy) to reduce training VRAM usage.
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4. Run the finetuning example:
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```bash
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axolotl train examples/internvl3_5/internvl3_5-8b-qlora.yml
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```
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This config uses about 8.21 GiB VRAM. Let us know how it goes. Happy finetuning! 🚀
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### Tips
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- You can run a full finetuning by removing the `adapter: qlora` and `load_in_4bit: true` from the config.
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- Read more on how to load your own dataset at [docs](https://docs.axolotl.ai/docs/dataset_loading.html).
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- The dataset format follows the multi-modal format as seen [here](https://docs.axolotl.ai/docs/multimodal.html#dataset-format).
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## Optimization Guides
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Please check the [Optimizations doc](https://docs.axolotl.ai/docs/optimizations.html).
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## Related Resources
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- [InternVL Paper](https://huggingface.co/papers/2508.18265)
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- [Axolotl Docs](https://docs.axolotl.ai)
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- [Axolotl Website](https://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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