{"id":13493323,"url":"https://github.com/ml-explore/mlx-examples","last_synced_at":"2025-05-13T15:04:57.298Z","repository":{"id":210796766,"uuid":"724855841","full_name":"ml-explore/mlx-examples","owner":"ml-explore","description":"Examples in the MLX framework","archived":false,"fork":false,"pushed_at":"2025-05-01T13:00:14.000Z","size":7670,"stargazers_count":7367,"open_issues_count":125,"forks_count":1041,"subscribers_count":81,"default_branch":"main","last_synced_at":"2025-05-06T14:49:28.555Z","etag":null,"topics":["mlx"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ml-explore.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2023-11-28T23:37:49.000Z","updated_at":"2025-05-06T10:16:40.000Z","dependencies_parsed_at":"2024-01-01T15:25:36.924Z","dependency_job_id":"d1676c15-5af5-4a8e-ae1a-10ea848546aa","html_url":"https://github.com/ml-explore/mlx-examples","commit_stats":null,"previous_names":["ml-explore/mlx-examples"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ml-explore%2Fmlx-examples","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ml-explore%2Fmlx-examples/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ml-explore%2Fmlx-examples/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ml-explore%2Fmlx-examples/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ml-explore","download_url":"https://codeload.github.com/ml-explore/mlx-examples/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253968954,"owners_count":21992261,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["mlx"],"created_at":"2024-07-31T19:01:14.173Z","updated_at":"2025-05-13T15:04:57.158Z","avatar_url":"https://github.com/ml-explore.png","language":"Python","funding_links":[],"categories":["Python","others","Repos","HarmonyOS","其他_机器学习与深度学习","Core MLX \u0026 Examples"],"sub_categories":["Windows Manager"],"readme":"# MLX Examples\n\nThis repo contains a variety of standalone examples using the [MLX\nframework](https://github.com/ml-explore/mlx).\n\nThe [MNIST](mnist) example is a good starting point to learn how to use MLX.\nSome more useful examples are listed below. Check-out [MLX\nLM](https://github.com/ml-explore/mlx-lm) for a more fully featured Python\npackage for LLMs with MLX.\n\n### Text Models \n\n- [Transformer language model](transformer_lm) training.\n- Minimal examples of large scale text generation with [LLaMA](llms/llama),\n  [Mistral](llms/mistral), and more in the [LLMs](llms) directory.\n- A mixture-of-experts (MoE) language model with [Mixtral 8x7B](llms/mixtral).\n- Parameter efficient fine-tuning with [LoRA or QLoRA](lora).\n- Text-to-text multi-task Transformers with [T5](t5).\n- Bidirectional language understanding with [BERT](bert).\n\n### Image Models \n\n- Generating images\n  - [FLUX](flux)\n  - [Stable Diffusion or SDXL](stable_diffusion)\n- Image classification using [ResNets on CIFAR-10](cifar).\n- Convolutional variational autoencoder [(CVAE) on MNIST](cvae).\n\n### Audio Models\n\n- Speech recognition with [OpenAI's Whisper](whisper).\n- Audio compression and generation with [Meta's EnCodec](encodec).\n- Music generation with [Meta's MusicGen](musicgen).\n\n### Multimodal models\n\n- Joint text and image embeddings with [CLIP](clip).\n- Text generation from image and text inputs with [LLaVA](llava).\n- Image segmentation with [Segment Anything (SAM)](segment_anything).\n\n### Other Models \n\n- Semi-supervised learning on graph-structured data with [GCN](gcn).\n- Real NVP [normalizing flow](normalizing_flow) for density estimation and\n  sampling.\n\n### Hugging Face\n\nYou can directly use or download converted checkpoints from the [MLX\nCommunity](https://huggingface.co/mlx-community) organization on Hugging Face.\nWe encourage you to join the community and [contribute new\nmodels](https://github.com/ml-explore/mlx-examples/issues/155).\n\n## Contributing \n\nWe are grateful for all of [our\ncontributors](ACKNOWLEDGMENTS.md#Individual-Contributors). If you contribute\nto MLX Examples and wish to be acknowledged, please add your name to the list in your\npull request.\n\n## Citing MLX Examples\n\nThe MLX software suite was initially developed with equal contribution by Awni\nHannun, Jagrit Digani, Angelos Katharopoulos, and Ronan Collobert. If you find\nMLX Examples useful in your research and wish to cite it, please use the following\nBibTex entry:\n\n```\n@software{mlx2023,\n  author = {Awni Hannun and Jagrit Digani and Angelos Katharopoulos and Ronan Collobert},\n  title = {{MLX}: Efficient and flexible machine learning on Apple silicon},\n  url = {https://github.com/ml-explore},\n  version = {0.0},\n  year = {2023},\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fml-explore%2Fmlx-examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fml-explore%2Fmlx-examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fml-explore%2Fmlx-examples/lists"}