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Support Mono-InternVL with PyTorch backend #2727
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OMG, we have so many typos... |
@zhulinJulia24 Please add Mono-InternVL into test cases |
One known bug is that Mono-InternVL encounters NaN when using float16 (this issue), due to some numerical instability. We will fix this in the next version of model, but for the current version I think float16 is not supported. Bfloat16 works fine. Should I add a note in I test KV INT 8 and INT 4 and they work fine. For W8A8 and W4A16 I suppose they are not supported, following InternVL2 PyTorchEngine. |
Sure. A note about this situation is appreciated. |
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LGTM
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LGTM
* support Mono-InternVL; fix typos * update readme * add assertion for FP16 * add assertion for FP16 * update _SUPPORTED_ARCHS
Support Mono-InternVL with Pytorch backend by creating
internlm2_ve.py
and addingis_mono
ininternvl.py
. The MoE structure is implemented withvision_embedding_indexing
andtext_embedding_indexing
. Also fix some typos.