Comments (1)
Thank you for your insightful question! I'm willing to answer this question as follows:
- Is it necessary to pre-train on LAION-2B?
The answer is no. We have found that simple audio pretraining can also make the network agnostic to some modalities.
- Can CLIP backbone work on various modalities?
We are not sure. Maybe these backbones are also compatible with the Meta-Transformer framework.
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Related Issues (20)
- video HOT 4
- Questions about experiments HOT 1
- Explain please HOT 2
- 为什么训练图像会出现这种错误 HOT 4
- Data2Seq > Hyper_Spectrum.py update from self.cls_tokens to self.cls_token HOT 1
- 请问使用 Data2seq的 tokenizer 时输入数据的格式 HOT 1
- 运行环境配置说明 HOT 1
- Hardware configurations for fine-tuning? HOT 1
- requirements HOT 2
- I have a question in the learning process. HOT 1
- Amount of embeddings HOT 1
- 下游任务的代码 HOT 1
- 使用metatransformer训练自己的数据集 HOT 1
- 图片格式转换(B,C,H,W) HOT 1
- meta-transformer能否进行三维CT或者核磁数据的分割和检测? HOT 2
- Data2Seq中的Vedio.py有问题 HOT 1
- Data2Seq for point cloud modality HOT 1
- Question in concating the features
- Pre-trained weights for Data2Seq
- Audio HOT 4
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