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| title: Apochat Gemma 4 E2B Trainer | |
| emoji: 🏋️ | |
| colorFrom: purple | |
| colorTo: pink | |
| sdk: gradio | |
| sdk_version: 4.0.0 | |
| app_file: app.py | |
| pinned: false | |
| # Apochat Gemma 4 E2B Trainer | |
| Fine-tune `google/gemma-4-E2B-it` on the Apochat chat dataset (`apoapps/apochat-gemma4-e2b-chat-v1`) | |
| using PEFT/LoRA. | |
| **You must upgrade the Space hardware to a GPU before starting training.** Free `cpu-basic` | |
| will not be able to train a 2B model in a reasonable time. | |
| Recommended hardware: | |
| - `t4-small` or `l4x1` for QLoRA. | |
| - `a10g-small` or larger for faster training. | |
| When training finishes, the adapter is pushed to `apoapps/apochat-gemma4-e2b-apochat-tuned-v2`. | |
| Use the LiteRT export script to convert the trained adapter + base model to `.litertlm`. | |