Comments (4)
This is something we're very interested in and still working on! We don't have a formula for it quite yet.
from m2.
This is something we're very interested in and still working on! We don't have a formula for it quite yet.
This doesn't sound like good news, it looks like I'll just have to CROSS ATTENTION mix MonarchMixer, is there a performance loss compared to raw ATTENTION?
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We've seen that we can match self-attention in quality with some gated convolutions (see the paper for details). Cross attention is still an open problem - which we'll be working on!
from m2.
We've seen that we can match self-attention in quality with some gated convolutions (see the paper for details). Cross attention is still an open problem - which we'll be working on!
If I use M2 can I not use positional coding as I feel that M2 looks a bit similar to conv which allows the model to know the positional information
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Related Issues (19)
- `python3 test_flash_mm.py` got error HOT 5
- Is there any detailed explanation of M2-VIT?
- What should I do if the √N is not an integer? HOT 3
- M2 model is applied on single image deraining model based on transformer HOT 5
- MNLI yaml config
- Missing Licence HOT 1
- does M2 work with ONNX? HOT 3
- Why is there such a big difference in cosine similarity between embeddings of the same pair when using padding=max_length versus padding=true? HOT 2
- Multilingual?
- precision on imagenet experiment HOT 1
- A question on square matrices
- LoCo Benchmark - BM25 & Insights HOT 5
- Code for projecting pre-trained BERT weights into Monarch matrices HOT 2
- Bert-like implementation HOT 4
- Some minor inconsistency in the paper HOT 2
- Code for model architecture
- Will M2-GPT be open-sourced? HOT 6
- MonarchMixerLayer HOT 1
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