Instructions to use vantuan5644/ucit-llava-1.5-7b-probes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vantuan5644/ucit-llava-1.5-7b-probes with PEFT:
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- Notebooks
- Google Colab
- Kaggle
UCIT continual instruction tuning β probes β LLaVA-1.5-7B
LoRA adapters trained sequentially on the 6-task UCIT benchmark, in this order:
ImageNet-R β ArxivQA β VizWiz-Caption β IconQA β CLEVR-Math β Flickr30k
Each <run>/Task<N>_<Name>/ holds the adapter after training task N,
so the full 6x6 forward-transfer matrix evaluates checkpoint N on every task K<=N.
The CLIP vision tower is frozen in every run here; non_lora_trainables.bin
carries the mm_projector only (21.0M parameters, no vision_tower.* keys).
Contents
| run | size | tasks |
|---|---|---|
ewc_lam1_ucit_llava |
1.5G | 3 |
ewc_lam5_ucit_llava |
1.5G | 3 |
ewc_lam1e5_ucit_llava |
1.5G | 3 |
ewc_ucit_llava_zero_fisher |
2.5G | 5 |
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liuhaotian/llava-v1.5-7b