Does this code support training baseline models (GME, LamRA) on private datasets?

Open
#191 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
35/100
Issue type
Documentation
Clarity
Needs clarification
Activity status
Stale
Tech stack
python
Domain
machine-learning

Research direction

Start with the train_v2_qwen2vl-2B_imageonly.sh script and trace the current training entry points for GME and LamRA. Determine how a private dataset can be used for both models and how their performance is evaluated; done means the repository has clear, reproducible instructions for these workflows.

Written by the indexing model from the issue text.

Description

I have my own dataset, and I've already completed LORA fine-tuning using the train_v2_qwen2vl-2B_imageonly.sh script from vlm2vec. However, I also want to evaluate the performance of GME and LamRA. How should I train them based on the current code?

Dominant language
Python
Stars
684
Forks
64
Avg merge
8m
Merged PRs (30d)
1

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from TIGER-AI-Lab/VLM2Vec

All issues in TIGER-AI-Lab/VLM2Vec

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.