base on Minimalistic 4D-parallelism distributed training framework for education purpose # picotron In the spirit of [NanoGPT](https://github.com/karpathy/nanoGPT), we created Picotron: The minimalist & most-hackable repository for pre-training Llama-like models with [4D Parallelism](https://arxiv.org/abs/2407.21783) (Data, Tensor, Pipeline, Context parallel). It is designed with simplicity and **educational** purposes in mind, making it an excellent tool for learning and experimentation.  - The code itself is simple and readable: `train.py`, `model.py` and `[data|tensor|pipeline|context]_parallel.py` are all under **300** lines of code. - Performance is not the best but still under active development. We observed 38% MFU on a LLaMA-2-7B model using 64 H100 GPUs and nearly 50% MFU on the SmolLM-1.7B model with 8 H100 GPUs. Benchmarks will come soon - Compared to [Nanotron](https://github.com/huggingface/nanotron/tree/main), Picotron is primarily for educational purposes, helping people quickly get familiar with all the techniques in distributed training # Tutorial videos - A step by step tutorial on how to build Picotron distributed training framework form scratch: - [Picotron tutorial (playlist)](https://www.youtube.com/playlist?list=PL-_armZiJvAnhcRr6yTJ0__f3Oi-LLi9S) 🎬 - [Picotron tutorial (codebase)](https://github.com/huggingface/picotron_tutorial) 👷🏻‍♂️ # Install ``` pip install -e . ``` # Quick start - Get a HF token [here](https://huggingface.co/settings/tokens) to download models from HuggingFace - GPU ```sh # To create a config file in json format under tmp by default python create_config.py --out_dir tmp --exp_name llama-1B --dp 8 --model_name HuggingFaceTB/SmolLM-1.7B --num_hidden_layers 15 --grad_acc_steps 32 --mbs 4 --seq_len 1024 --hf_token <HF_TOKEN> # Locally torchrun --nproc_per_node 8 train.py --config tmp/llama-1B/config.json # 3D Parallelism python create_config.py --out_dir tmp --dp 4 --tp 2 --pp 2 --pp_engine 1f1b --exp_name llama-7B --model_name meta-llama/Llama-2-7b-hf --grad_acc_steps 32 --mbs 4 --seq_len 1024 --hf_token <HF_TOKEN> # Slurm python submit_slurm_jobs.py --inp_dir tmp/llama-7B --qos high --hf_token <HF_TOKEN> ``` - CPU (expect it to be slow) ```sh # 3D Parallelism on CPU python create_config.py --out_dir tmp --exp_name llama-1B-cpu --dp 2 --tp 2 --pp 2 --pp_engine 1f1b --model_name HuggingFaceTB/SmolLM-1.7B --num_hidden_layers 5 --grad_acc_steps 2 --mbs 4 --seq_len 128 --hf_token <HF_TOKEN> --use_cpu # Locally torchrun --nproc_per_node 8 train.py --config tmp/llama-1B-cpu/config.json ``` # Citation If you use Picotron, please cite it as: ```bibtex @misc{zhao2025picotron, author = {Haojun Zhao and Ferdinand Mom}, title = {Picotron: Distributed training framework for education and research experimentation}, year = {2025}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/huggingface/picotron}} } ``` # Acknowledgements - [Megatron-LM](https://github.com/NVIDIA/Megatron-LM) - [FairScale](https://github.com/facebookresearch/fairscale) - [LitGPT](https://github.com/Lightning-AI/lit-gpt) ", Assign "at most 3 tags" to the expected json: {"id":"12684","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"