A new argument "--max_seq_length" has been added to the command-line parser and passed as a parameter to the main function of the lora.py script. This allows users to specify and control the maximum sequence length during training.
* Add grad checkpointing and PE in the transformer example
* Remove other frameworks from LM example
* Remove the other frameworks from MNIST example
* Improve the transformer LM example
* Fix black and change LR
* Decoding results in garbled text when multiple tokens represent a single character (e.g., Chinese).
* Decoding results in garbled text when multiple tokens represent a single character (e.g., Chinese).
* LoRA: Remove unnecessary model type judgments
1. Supported models are already checked in the load_model function in utils, no need to repeat the check in lora
2. The checks in lora are not synchronized with those in utils
* LoRA: add LoRA supported models in mlx_lm utils
* feat(mlx-lm): add de-quant for fuse
* chore: disable quant in to linear when de-quant enabled
* chore: add better error handling for adapter file not found
* chore(mlx-lm): pass max seq len to evaluate in training loop
* chore: make sure the batch seq not exceed max len
* chore: update comment
* chore: add warning before truncate input
* Draft of tiny llama from gguf
* Transpose all
* No transposition with new layout
* Read config from gguf
* Create tokenizer from gguf
* move gguf and update to be similar to hf_llm
* change model to HF style + updates to REAMDE
* nits in REAMDE
* nit readme
* only use mlx for metadata
* fix eos/bos tokenizer
* fix tokenization
* quantization runs
* 8-bit works
* tokenizer fix
* bump mlx version
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Co-authored-by: Juarez Bochi <juarez.bochi@grammarly.com>
Co-authored-by: Awni Hannun <awni@apple.com>
* fix the chinese character generation as same as PR #321
* reuse the generate logic to utils.py
* format
* verbose defualt
* fix conflicst with colorize and character check
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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
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Co-authored-by: Shunta Saito <shunta@mitmul-mbp.local>
Co-authored-by: Awni Hannun <awni@apple.com>
* Add colorized output option to generate script
Two new functions were added to the script that allow output to be colorized based on the T[0] probability. Changes were made to the `generate_step` function in utils.py to permit colorization. Additionally, an argument for colorization was introduced to the command-line parser.
* Rename 'colorize' parameter with 'return_probability' in generate_step
* add an option to apply the tokenizer chat template
* fix the option to apply the tokenizer chat template
* better error messages for chat template issues
* apply the chat template by default when possible
* nit in comment'
* rebase
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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
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Co-authored-by: Awni Hannun <awni@apple.com>
* Implement normalizing flow Real NVP example
* Add requirements and basic usage to normalizing flow example
* Minor changes to README in normalizing flow example
* Remove trailing commas in function arguments for unified formatting in flows example
* Fix minor typos, add some annotations
* format + nits in README
* readme fix
* mov, minor changes in main, copywright
* remove debug
* fix
* Simplified class structure in distributions; better code re-use in bijectors
* Remove rogue space
* change name again
* nits
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Co-authored-by: Awni Hannun <awni@apple.com>
* Add missing keyword to the decoding options
* Reverting last commit
* Fixing transcribe keyword in benckmark.py
* Add argument name to load_model
This is intended to avoid confusion
