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I am running experiments using OpenCLIP model from mlfoundations. . It turns out that openCLIP's architecture is different from CLIP's architecture you defined. I encountered the same error as mentioned here, then tried to add missing parts but somehow still get attn_probs = None at the end, instead of being a tensor calculated along the way.
Could you please guide me on how to make your code work with openCLIP? In particular, what should be enough to modify in respective modules of openCLIP ( transformer.py is the equivalent module to yours model.py).
P.S. if you are interested in working on this for an hourly-based compensation, I would gladly discuss it. Please let me know.
The text was updated successfully, but these errors were encountered:
tahirmiri
changed the title
adding self.attn_probs in ResidualAttentionBlock() of mlfoundations / open_clip model
adding self.attn_probs in ResidualAttentionBlock() of mlfoundations / open_clip model doesn't work
May 31, 2023
tahirmiri
changed the title
adding self.attn_probs in ResidualAttentionBlock() of mlfoundations / open_clip model doesn't work
self.attn_probs in ResidualAttentionBlock() causes problems - how to make explainability work with mlfoundations / open_clip model
Jun 9, 2023
Hi,
I am running experiments using OpenCLIP model from mlfoundations. . It turns out that openCLIP's architecture is different from CLIP's architecture you defined. I encountered the same error as mentioned here, then tried to add missing parts but somehow still get attn_probs = None at the end, instead of being a tensor calculated along the way.
Could you please guide me on how to make your code work with openCLIP? In particular, what should be enough to modify in respective modules of openCLIP ( transformer.py is the equivalent module to yours model.py).
P.S. if you are interested in working on this for an hourly-based compensation, I would gladly discuss it. Please let me know.
The text was updated successfully, but these errors were encountered: