* initial batch generation
* more in batch generate
* concatenation
* use batch API in eval
* unique max tokens per prompt
* basic continuous batching
* simplify
* better perf by ensuring everything in same stream
* use data class for response
* check cache type
* add swanlab tracker support
* add key features line for swanlab&wandb
* Fix potential bug reported in #316
* Refactor logging configuration to support multiple reporting services
* update LORA.md docs: unify logging configuration with --report_to flag
* Fix flags and error on unknown service
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* 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
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* Adding full model weights finetuning
* Updating the LORA.md and ACKNOWLEDGMENTS.md files.
* removing --use-dora and --fulll-training and adding --fine-tune-type
* some clean up
* reformating and fixing dora training
* updated CONFIG_DEFAULTS
* update config example
* update in the config example fie
* Update LORA.md
* merge and commit
* adding argument for dora linear layer
* clean up
* clean up in the example yaml file
* fix
* final fix before sending
* small addition to re md file
* fix for loading the fully trained model by saving all the files and configs correctly
* clean up
* removing the unnesesairy files
* changing lora layers back to 16
* removed max file size
* nits
* resolve merge
* some consistency changes
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* Generate response with optional arguments
* Reference response generation example
* Include transformers and sentencepiece
* Update example to run Mistral-7B-Instruct-v0.3
* Link to generation example
* Style changes from pre-commit
* Add Starcoder2 model and update utils.py
* Refactor model arguments and modules in starcoder2.py
* Refactor FeedForward class to MLP in starcoder2.py
* Fix typo
* pre-commit
* Refactor starcoder2.py: Update model arguments and modules
* Fix LM head and MLP layers
* Rename input layer norm
* Update bias in linear layers
* Refactor token embeddings in Starcoder2Model
* Rename to standard HF attention layer name
* Add LayerNorm
* Add transposed token embeddings (like in Gemma)
* Refactor MLP and TransformerBlock classes
* Add tie_word_embeddings option to ModelArgs and update Model implementation
* Add conditional check for tying word embeddings in Starcoder2Model
* Fix bias in lm_head linear layer
* Remove unused LayerNorm in stablelm
* Update transformers dependency to use GitHub repository
* fix lm head bug, revert transformer req
* Update RoPE initialization in Attention class
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* Convert HF weights of PLaMo and load it to a plamo model in mlx
* Fix model inference part
* Add bos at the beginning of the prompt
* Fix convert.py to copy tokenizer.model into the converted dir
* Use the required insturction format in generate.py when "--instruct" option is specified
* Change filenames and update existing scripts
* Add README
* Add requirements.txt
* Fix plamo.py to stop generation when EOS appears
* Add quantization to convert.py
* Use mlx>=0.0.9 for mx.core.outer() in PLaMo model
* Update acknowledgements.md
* Fix card text in upload_to_hub()
* Not use prompt template when --instruct is not specified
* Ask if you trust_remote_code for loading tokenizer of PLaMo
* Check the user trusts the remote code when converting
* Remove plamo directory
* Update README
* Add PLaMo model file
* Fix the handling of cache in PLaMo and update README
* Ask if trust_remote_code only when the model is PLaMo
* Remove resolve_trust_remote_code from convert.py and use the latest transformers
* Remove code not to add EOS
* Update README to fix an example not to use noncommercial version of the model
* Remove unused imports
* Remove unnecessary description about the instruct model of PLaMo from README
* format, nits in README
* typo
---------
Co-authored-by: Shunta Saito <shunta@mitmul-mbp.local>
Co-authored-by: Awni Hannun <awni@apple.com>
* refactor(qwen): moving qwen into mlx-lm
* chore: update doc
* chore: fix type hint
* add qwen model support in convert
* chore: fix doc
* chore: only load model in quantize_model
* chore: make the convert script only copy tokenizer files instead of load it and save
* chore: update docstring
* chore: remove unnecessary try catch
* chore: clean up for tokenizer and update transformers 4.37
* nits in README
---------
Co-authored-by: Awni Hannun <awni@apple.com>
jaycoolslm