Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

I encountered a warning #29

Open
ctxya1207 opened this issue Aug 4, 2024 · 0 comments
Open

I encountered a warning #29

ctxya1207 opened this issue Aug 4, 2024 · 0 comments

Comments

@ctxya1207
Copy link

Instantiating LlamaAttention without passing layer_idx is not recommended and will to errors during the forward call, if caching is used. Please make sure to provide a layer_idx when creating this class.
Loading checkpoint shards: 100%|██████████| 33/33 [00:22<00:00, 1.47it/s]
Some weights of MPLUGOwl2LlamaForCausalLM were not initialized from the model checkpoint at D:\桌面\mplug_owl2_7b_448_qinstruct_preview_v0.1 and are newly initialized: ['model.visual_abstractor.encoder.layers.4.crossattention.attention.k_pos_embed', 'model.visual_abstractor.encoder.layers.0.crossattention.attention.q_pos_embed', 'model.visual_abstractor.encoder.layers.5.crossattention.attention.k_pos_embed', 'model.visual_abstractor.encoder.layers.5.crossattention.attention.q_pos_embed', 'model.visual_abstractor.encoder.layers.2.crossattention.attention.k_pos_embed', 'model.visual_abstractor.encoder.layers.1.crossattention.attention.q_pos_embed', 'model.visual_abstractor.encoder.layers.3.crossattention.attention.q_pos_embed', 'model.visual_abstractor.encoder.layers.4.crossattention.attention.q_pos_embed', 'model.visual_abstractor.encoder.layers.0.crossattention.attention.k_pos_embed', 'model.visual_abstractor.encoder.layers.2.crossattention.attention.q_pos_embed', 'model.visual_abstractor.encoder.layers.3.crossattention.attention.k_pos_embed', 'model.visual_abstractor.encoder.layers.1.crossattention.attention.k_pos_embed']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu.
Evaluating [E:\Project\Q-Align-main\playground\data\test_jsons\AGIQA-3K.json]: 100%|██████████| 2982/2982 [24:42<00:00, 2.01it/s]

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant