Comments (1)
Yes of course. The easist way is to prepare your custom dataset into the same format of OKVQA.
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Related Issues (20)
- The process of image caption
- Checkpoints Availability HOT 2
- assets HOT 1
- Replacing GPT-3 with other academic LLMs HOT 8
- KeyError: 179520 ?? HOT 13
- 当我运行bash scripts/extract_img_feats.sh时显示下面内容,但并没有生成coco2014_feats HOT 7
- The first candidate answer of your provided candidates_okvqa.json in assets.zip HOT 3
- 当我在训练stage1时预训练、微调和生成候选答案时报了一样的错OSError: We couldn't connect to 'https://huggingface.co' to load this file, couldn't find it in the HOT 4
- 当我运行stage2的命令时,显示错误连接openAI,这个是什么原因呢? HOT 1
- 当我在训练stage1时预训练、微调和生成候选答案时报了一样的错 TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType 请问该怎么解决呢 HOT 1
- Trained model HOT 1
- okvqa-stage1-pretrain HOT 3
- OpenAI-Api Cost HOT 1
- skip step 1 and go directly to step 2 HOT 1
- 1
- Accuracy does not increased HOT 1
- Naive question on OK-VQA and A-OKVQA evaluation.
- Huggingface model HOT 1
- Hello, may I ask how you avoid the problem of large explanatory texts in the answers generated by chat3.5. HOT 2
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