243620394a
* fix: force train split for json,csv,txt for test_datasets * feat(doc): add info on mixing datasets for VLM * feat(doc): max memory * fix(doc): clarify lr groups * fix: add info on vision not being dropped * feat: add qwen3-vl to multimodal docs * fix: add moe blocks to arch list * feat(doc): improve mistral docs * chore: add helpful link [skip-e2e] * fix: add vram usage for mistral small * Update link in docs/faq.qmd Co-authored-by: salman <salman.mohammadi@outlook.com> --------- Co-authored-by: Wing Lian <wing@axolotl.ai> Co-authored-by: salman <salman.mohammadi@outlook.com>
61 lines
1.9 KiB
Markdown
61 lines
1.9 KiB
Markdown
# Magistral Small Vision Fine-tuning
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This guide covers fine-tuning [Magistral Small 2509](https://huggingface.co/mistralai/Magistral-Small-2509) with vision capabilities using Axolotl.
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## Prerequisites
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Before starting, ensure you have:
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- Installed Axolotl from source (see [main README](../README.md#getting-started))
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## Getting started
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1. Install the required vision lib:
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```bash
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pip install 'mistral-common[opencv]==1.8.5'
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```
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2. Download the example dataset image:
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```bash
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wget https://huggingface.co/datasets/Nanobit/text-vision-2k-test/resolve/main/African_elephant.jpg
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```
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3. Run the fine-tuning:
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```bash
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axolotl train examples/magistral/vision/magistral-small-vision-24B-qlora.yml
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```
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This config uses about 17GiB VRAM.
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WARNING: The loss and grad norm will be much higher than normal at first. We suspect this to be inherent to the model as of the moment. If anyone would like to submit a fix for this, we are happy to take a look.
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### Tips
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Key differences from text-only model:
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- `max_tokens: 131072` for inference
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- Multi-modal dataset format required
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- Sample packing not supported
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## Dataset Format
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The vision model requires multi-modal dataset format as documented [here](https://docs.axolotl.ai/docs/multimodal.html#dataset-format).
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One exception is that, passing `"image": PIL.Image` is not supported. MistralTokenizer only supports `path`, `url`, and `base64` for now.
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Example:
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```json
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{
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"messages": [
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{"role": "system", "content": [{ "type": "text", "text": "{SYSTEM_PROMPT}"}]},
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{"role": "user", "content": [
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{ "type": "text", "text": "What's in this image?"},
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{"type": "image", "path": "path/to/image.jpg" }
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]},
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{"role": "assistant", "content": [{ "type": "text", "text": "..." }]},
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],
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}
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```
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## Limitations
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- Sample Packing is not supported for multi-modality training currently.
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