* fix rotating kv cache for chat use case
* reorg + fixes to caching, unify prompt caching across types and use cases for e.g. caching during a chat
* nit in chat
* fix tests
* fix tests
* fix tests
* docs
* chat command
* comments + docs
* Define meta_state on all Cache implementations
* fixes + trim_prompt_cache api
* fix default model
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Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* initial commit
* initial commit
* Adding first lines
* adding x, and dt projection layers
* adding the clamping mechanism
* First succesful inference
* last commit for today - added custom geenrate function and it works as expected, will try training and then with loading a model from the hub
* clean up
* save up
* almost
* update
* update
* fixed cache handeling
* fixed loading
* added seperate generat_step method in the model and also in the utils to automaticaly use the generate step mthod in the model class
* quick update
* still not working
* save
* still not working
* initial commit
* utils.py logits = logits[:, -1, :] TypeError: tuple indices must be integers or slices, not tuple
* update
* update
* Fixing the Batching Depfwise Comnvolution and multi token input
* fixing generate and logits outputs
* Done!
* Fixing the cache handling, generating works now trying training
* update ACKNOWLEDGEMENTS
* removing the model_type if stuff in the _step loop in generate_step and adding MambaCache in base.py for training easier generations and removing mamba in tuner/utils.
* quick clean up
* update trainer/utils for right initialisation of the layers for LoRA, but not working.
* clean up
* Forther update to trainer/utils for correct layer selection. Successfull training
* removing extra mamba-infer.py file
* clean up, reformating will come later
* reformat and big clean up, final commit
* some speedups and cleanups
* fix test
* nits
* nits
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Co-authored-by: Awni Hannun <awni@apple.com>
