Comments (3)
Hi @filippo82, I think it could be cool to add distillation loss of course. I plan to improve the loss function of the train module in the following weeks, there won't be any breaking change.
Before releasing the centroids algorithm of ColBERTV2 I plan to release another method to accelerate ColBERT retriever, it will be really fast and still accurate, work in progress.
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Hi @raphaelsty 👋🏻 thanks a lot for your reply and sorry for the slooow reply.
Let me know if there is any way I can help with testing/debugging.
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Hi @filippo82, I did release neural-cherche 1.1.0 which improve loss stability and brings better default parameters to models. Also I did release neural-tree in order to accelerate ColBERT.
Feel free to open a PR in neural-cherche if you are interested in Knowledge Distillation
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Related Issues (9)
- License HOT 2
- Mismatch in documents embeddings size HOT 1
- Load the triplets input incrementally HOT 2
- could you please explain the rational behind applying clip on ranking loss HOT 2
- What is licence of the splade/sparsembed models hosted in huggingface? HOT 8
- DeepImpact implementation HOT 1
- How to train ColBERT model on a lot of data? HOT 1
- How did you train SparseEmbed? HOT 2
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