DAMO-NLP-SG / DAMO-NLP-SG/VideoLLaMA2
how to finetune Videollama2 chat models using QLoRA and LoRA.
- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 90
- PR merge metrics
- No merged PRs in 30d
Description
how to finetune Videollama2 chat models using QLoRA and LoRA.
...
--data_path datasets/custom_sft/custom.json
--data_folder datasets/custom_sft/
--pretrain_mm_mlp_adapter CONNECTOR_DOWNLOAD_PATH (e.g., DAMO-NLP-SG/VideoLLaMA2-7B-Base)
...
here you have mentioned only the base models.
Contributor guide
No contributing guide indexed for this repository
Research direction
Start with the fine-tuning command fragments in the issue, especially datasets/custom_sft/custom.json, datasets/custom_sft/, and the pretrain_mm_mlp_adapter value. Document the missing chat-model procedure for QLoRA and LoRA, including how the referenced model paths should be used, and verify that the resulting instructions are complete.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100