mlx-examples/ACKNOWLEDGMENTS.md

# Individual Contributors

If you wish to be acknowledged for your contributions, please list your name
with a short description of your contribution(s) below. For example:

- Jane Smith: Added the `foo` example.

MLX Examples was developed with contributions from the following individuals:

- Juarez Bochi: Added support for T5 models.
- Sarthak Yadav: Added the `cifar` and `speechcommands` examples.
- Shunta Saito: Added support for PLaMo models.
- Gabrijel Boduljak: Implemented `CLIP`.
- Markus Enzweiler: Added the `cvae` examples.
- Prince Canuma: Helped add support for `Starcoder2` models.
- Shiyu Li: Added the `Segment Anything Model`.
- Gökdeniz Gülmez: Added support for `MiniCPM` and `Mamba`.
Citation + contributor acknowledgments section (#136) * citation + acks section * nits 2023-12-19 02:12:35 +08:00			`# Individual Contributors`

			`If you wish to be acknowledged for your contributions, please list your name`
			`with a short description of your contribution(s) below. For example:`

			- Jane Smith: Added the `foo` example.

			`MLX Examples was developed with contributions from the following individuals:`
T5: Change default dtype to bfloat16 (#147) * T5: Change default to bfloat16 * Add myself to contributors * t5: Change convert.py default to float32 2023-12-20 05:44:36 +08:00
			`- Juarez Bochi: Added support for T5 models.`
Add PLaMo-13B model as an LLM example (#303) * 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> 2024-01-23 23:17:24 +08:00			- Sarthak Yadav: Added the `cifar` and `speechcommands` examples.
			`- Shunta Saito: Added support for PLaMo models.`
CLIP (ViT) (#315) * probably approximatelly correct CLIPTextEncoder * implemented CLIPEncoderLayer as built-in nn.TransformerEncoderLayer * replaced embedding layer with simple matrix * implemented ViT * added ViT tests * fixed tests * added pooler_output for text * implemented complete CLIPModel * implemented init * implemented convert.py and from_pretrained * fixed some minor bugs and added the README.md * removed tokenizer unused comments * removed unused deps * updated ACKNOWLEDGEMENTS.md * Feat: Image Processor for CLIP (#1) @nkasmanoff: * clip image processor * added example usage * refactored image preprocessing * deleted unused image_config.py * removed preprocessing port * added dependency to mlx-data * fixed attribution and moved photos to assets * implemented a simple port of CLIPImageProcessor * review changes * PR review changes * renamed too verbose arg * updated README.md * nits in readme / conversion * simplify some stuff, remove unneeded inits * remove more init stuff * more simplify * make test a unit test * update main readme * readme nits --------- Co-authored-by: Noah Kasmanoff <nkasmanoff@gmail.com> Co-authored-by: Awni Hannun <awni@apple.com> 2024-02-01 06:19:53 +08:00			- Gabrijel Boduljak: Implemented `CLIP`.
Example of a Convolutional Variational Autoencoder (CVAE) on MNIST (#264) * initial commit * style fixes * update of ACKNOWLEDGMENTS * fixed comment * minor refactoring; removed unused imports * added cifar and cvae to top-level README.md * removed mention of cuda/mps in argparse * fixed training status output * load_weights() with strict=True * pretrained model update * fixed imports and style * requires mlx>=0.0.9 * updated with results using mlx 0.0.9 * removed mention of private repo * simplify and combine to one file, more consistency with other exmaples * few more nits * nits * spell * format --------- Co-authored-by: Awni Hannun <awni@apple.com> 2024-02-07 12:02:27 +08:00			- Markus Enzweiler: Added the `cvae` examples.
Starcoder2: Update config and change GQA to use repeat (#520) * update config * change gqa to use repeat instead of concante * contribution 2024-03-03 22:12:03 +08:00			- Prince Canuma: Helped add support for `Starcoder2` models.
Segment Anything Model (#552) * add segment anything model * add readme * reorg file structure * update * lint * minor updates * ack * fix weight loading * simplify * fix to run notebooks * amg in mlx * remove torch dependency * nit in README * return indices in nms * simplify * bugfix / simplify * fix bug' * simplify * fix notebook and remove output * couple more nits --------- Co-authored-by: Awni Hannun <awni@apple.com> 2024-06-03 07:45:51 +08:00			- Shiyu Li: Added the `Segment Anything Model`.
Adding support for mamba (#940) * 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 --------- Co-authored-by: Awni Hannun <awni@apple.com> 2024-09-28 22:02:53 +08:00			- Gökdeniz Gülmez: Added support for `MiniCPM` and `Mamba`.