Deepspeed github. - microsoft/DeepSpeed .



    • ● Deepspeed github pip install . DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU: DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. ops. Hardware cost-effectiveness: Given the price that InfiniBand (IB) is usually more expensive than ethernet, 200 to 400/800 Gbps ethernet link AllTalk is based on the Coqui TTS engine, similar to the Coqui_tts extension for Text generation webUI, however supports a variety of advanced features, such as a settings page, low VRAM support, DeepSpeed, narrator, model finetuning, custom models, wav file maintenance. - Workflow runs · microsoft/DeepSpeed DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. We have found this library to be very portable across environments with NVIDIA GPUs with compute capabilities 8. All gists Back to GitHub Sign in Sign up Sign in Sign up You signed in with another tab or window. The issue has been reported to the pytorch team and it should be fixed in the next release. Code Issues Pull You signed in with another tab or window. This article describes the method I successfully used to resolve the issue of deepspeed. On the right is an example of DeepSpeed-VisualChat. Optimized checkpointing engine for DeepSpeed/Megatron. To get started, please visit our GitHub page for DeepSpeed-MII: GitHub Landing Page; DeepSpeed-FastGen is part of the bigger DeepSpeed ecosystem comprising a multitude of Deep Learning systems and modeling technologies. Acknowledgments and Contributions . More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. GitHub community articles Repositories. After a simple search, I noticed that it seems no one has mentioned this before, so I decided to leave some traces here for future reference for others. Describe the bug Alpaca start with too large loss in v0. To learn more, Please visit our website for detailed blog posts, tutorials, and helpful documentation. Contribute to microsoft/DeepSpeedExamples development by creating an account on GitHub. - microsoft/DeepSpeed. Since my patch in Example models using DeepSpeed. 26 # activate environment conda activate DeepSpeed # install compiler conda install compilers sysroot_linux-64==2. Contribute to bobo0810/MiniGPT-4-DeepSpeed development by creating an account on GitHub. Alpaca initializes word embedding like this: def smart_tokenizer_and_embedding_resize( special_tokens_dict: Dict, tokenizer: transformers. I introduced a PR in #4496. Reload to refresh your session. We thank the collaboration of the University of Sydney and Rutgers University. ") when trying to run deepspeed inference on cpu (target model: Qwen2-7B-Instruct) To Reproduce Step Explore the GitHub Discussions forum for microsoft DeepSpeed. After receiving the PRs, we will review them and merge them after necessary tests/fixes. Ongoing research training transformer language models at scale, including: BERT & GPT-2 - Releases · microsoft/Megatron-DeepSpeed DeepSpeed brings together innovations in parallelism technology such as tensor, pipeline, expert and ZeRO-parallelism, and combines them with high performance custom inference kernels, communication optimizations and heterogeneous memory technologies to enable inference at an unprecedented scale, while achieving unparalleled latency, throughput and cost reduction. GPT-NeoX-20B (currently the only pretrained model we provide) is a very large model. Can you comment? Thanks! @mrwyattii-- You're correct!Looks like a typo. Sign up for GitHub Please note that both Megatron-LM and DeepSpeed have Pipeline Parallelism and BF16 Optimizer implementations, but we used the ones from DeepSpeed as they are integrated with ZeRO. init_inference and zero stage 3 in your codes, which are not recommended combinations. ipynb. grad directly fails while tracing the mod In this tutorial we describe how to use DeepSpeed Sparse Attention (SA) and its building-block kernels. This library is not intended to be an independent user package, but is open-source to benefit the community and show how DeepSpeed is accelerating DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. Docker context Are you using a specific docker image that you can share? N/a. sh script in the repo. Describe the bug Hi, i run deepspeed inference for llama3. FastGen for latency/throughput scenarios: independent of zero stage 3. This library is not intended to be an independent user package, but is open-source to benefit the community and show how DeepSpeed is accelerating DeepSpeed brings together innovations in parallelism technology such as tensor, pipeline, expert and ZeRO-parallelism, and combines them with high performance custom inference kernels, communication optimizations and heterogeneous memory technologies to enable inference at an unprecedented scale, while achieving unparalleled latency, throughput and cost reduction. AI-powered developer Contribute to gouqi666/DPO-deepspeed development by creating an account on GitHub. py --deepspeed. Sign up for GitHub DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. Although technically the warning is correct as it says "The default cache directory" it is also very misleading as it is irrelevant when TRITON_CACHE_DIR is set to a non-NFS directory. @tjruwase Tasks ZeRO3 support (#4878, we currently break the graph to make communication collectives work) Pipeline parallel support (#4677 DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. compile. See the next section for more details on this. AI-powered developer I would like to know in which modules DeepSpeed has utilized the latest PyTorch 2. The last batch norm initialization after the deepspeed. The weights alone take up around 40GB in GPU memory and, due to the tensor parallelism scheme as well as the high memory usage, you will need at minimum 2 GPUs with a total of ~45GB of GPU VRAM to run inference, and significantly more for training. It can automatically take your favorite pre-trained large language models through an OpenAI InstructGPT style three stages to produce your Are you launching your experiment with the deepspeed launcher, MPI, or something else? No, using srun torchrun train. The matter seems to have been resolved. 1 and it was working fine but installing the latest deepspeed (any version from 0. I use ZeRO-3 without offloading, with huggingFace trainer. AI-powered developer Now, we utilize the torch. I wanted to check that WarmupDecayLR. With DeepSpeed you can: Features include mixed precision training, single-GPU, multi-GPU, and multi-node training as well as custom model parallelism. 13. launch + Deepspeed + Huggingface trainer API to fine tunig Flan-T5-XXL on AWS SageMaker for multiple nodes (Just set the environment variable "NODE_NUMBER" to 1, you can use the same codes for multiple GPUs training on single node). Bug description Context: Running inference on a multi-modal LLM , at each decoding step parts of the network are used and depends on the input modality at each step. Automate any workflow Codespaces GitHub is where people build software. Install the DeepSpeed teacher checkpoints from here to perform fast loading as described here. Describe the bug I encountered an issue when using DeepSpeed 0. Code Issues Pull DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. Unfortunately the model is not DeepSpeed is a library designed for speed and scale for distributed training of large models with billions of parameters. If you'd like regular pip install, checkout the latest stable version (v4. Sign in Product GitHub Copilot. Sign up for GitHub By clicking “Sign up for GitHub”, DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. AI-powered developer Hi @guoyunqingyue - compute capability 6. Step 3 Contribute to AlongWY/deepspeed_wheels development by creating an account on GitHub. More than 100 million people use GitHub to discover, fork, Train llm (bloom and llama) with deepspeed pipeline mode. Minimal Code Change. Write better code with AI Security. This is making testing code with deepspeed extremely complicated I can't explain t In the spirit of democratizing ChatGPT-style models and their capabilities, DeepSpeed is proud to introduce a general system framework for enabling an end-to-end training experience for ChatGPT-like models, named DeepSpeed Chat. Recently we encounter a problem with deepspeed. Contribute to hemildesai/deepspeed_mmdetection3d development by creating an account on GitHub. param_names[lp] param Sign up for a free GitHub account to open an issue and contact its maintainers and thinking more about it, i can see maybe some concerns with initializing the ema_model with copy. Has it incorporated features related to PyTorch 2. Skip to content. WANDB_MODE=offline deepspeed --num_gpus Greetings, This is my first time using deepspeed. At its core is the Zero Redundancy Optimizer (ZeRO) that shards optimizer states (ZeRO-1), gradients (ZeRO-2), and parameters (ZeRO-3) Example models using DeepSpeed. 5 (I am not a sudoer of the server so I am not able to upgrade the toolkit, instead I have created a conda environment and installed CUDA toolkit 11. Given the amount of merged commits, bugs can happen in the cases that we haven't tested, and your contribution (bug report, bug fix pull request) is highly welcomed. 5-MoE-A2. Topics Trending Collections Enterprise Enterprise platform. bat, I get a deepspeed whl file finnally. 🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed suppo DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. 04, CUDA toolkit is 11. Discuss code, ask questions & collaborate with the developer community. md at master · microsoft/DeepSpeed You signed in with another tab or window. [rank2]: pydantic_core. yes, i want to use clip_grad_norm when use deepspeed stage 2,and i set "gradient_clipping": 1. AI DeepSpeed-Kernels is a backend library that is used to power DeepSpeed-FastGen to achieve accelerated text-generation inference through DeepSpeed-MII. 3 on a RTX A6000 GPU (on a server) so compute capability is met, ubuntu is 22. Automate any workflow Codespaces With DeepSpeed, there are more configuration parameters that could potentially affect the training speed, thus making it more tedious to manually tune the configuration. The tl;dr answer is, to get reasonable GPU throughput when training at scale (64+GPUs), 100 Gbps is not enough, 200-400 Gbps is ok, 800-1000 Gbps will be ideal. In my second step, deepspeed goes ahead and fetches I am running into the error, which seems to occure inside the deepspeed stage_1_and_2. Ascend is a full-stack AI computing infrastructure for industry applications and services based on Huawei Ascend processors and software. However, when I ran the program, the following issue occurred File "D: Sign up for a free GitHub account to open an issue and contact its maintainers and the community. 1. Automate any workflow Codespaces Figure 1. When @Quentin-Anthony and I used the PyTorch memory profiler with DS, we saw that buffers allocated during the backwards pass by torch. Curate this topic Add this topic to your repo To associate your Example models using DeepSpeed. 1, Sign up for a free GitHub account to open an issue and contact its maintainers and the community. 9. Hi, we're OpenRLHF team, we heavily use deepspeed to build our RLHF framework and really appreciate to your great work. DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. Contribute to git-cloner/llama2-lora-fine-tuning development by creating an account on GitHub. adam import DeepSpeedCPUAdam fused_adam = DeepSpeedCPUAdam([torch. deepcopy. json file gives the user the ability to specify DeepSpeed options in terms of batch size, micro batch size, learning rate, and other parameters. 0+ (Ampere+), CUDA Edit - 1 The same problem occurs when using ZeRO2 with offloading. initialize() on model, there could be a dtype mismatch due to mixed precision with fp16/bf16 that i'm training the model in, and the ema_model will be still on fp32, so maybe the In July 2023, we had a sync with the NVIDIA/Megatron-LM repo (where this repo is forked from) by git-merging 1100+ commits. AI-powered developer You signed in with another tab or window. We’re on a journey to advance and democratize artificial Ulysses-Offload has been fully integrated with Megatron-DeepSpeed and accessible through both DeepSpeed and Megatron-DeepSpeed GitHub repos. See examples of DeepSpeed integration with HuggingFace It is an easy-to-use deep learning optimization software suite that powers unprecedented scale and speed for both training and inference. @phalexo-- I believe the cause of your issue is that torch. You switched accounts on another tab or window. DeepSpeed enables world’s most powerful language models like MT-530B BLOOM. 47. Sign up for a free GitHub account to open an issue and contact its maintainers and You signed in with another tab or window. CANN (Compute Architecture of Neural Networks), developped by Huawei, is a heterogeneous computing architecture for AI. Browse the latest releases, features, bug fixes, and contributors on GitHub. py, in addition to the --deepspeed flag to enable DeepSpeed, the appropriate DeepSpeed configuration file must be specified using --deepspeed_config I noticed the use of deepspeed. initialize() hanging. 8). We invite the community to explore our implementation, contribute to further advancements, and join us in pushing the boundaries of what is possible in LLM and AI. py line 508 - 509: lp_name = self. Find and fix DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. Automate any workflow Codespaces ` deepspeed_inclusion_filter `: DeepSpeed inclusion filter string when using mutli-node setup. 10x Larger Models. _pydantic_core. AI-powered developer GitHub is where people build software. DeepSpeed brings together innovations in parallelism technology such as tensor, pipeline, expert and ZeRO-parallelism, and combines them with high performance custom inference kernels, communication optimizations and heterogeneous memory technologies to enable inference at an unprecedented scale, while achieving unparalleled latency, throughput and cost reduction. Contribute to X-jun-0130/LLM-Pretrain-FineTune development by creating an account on GitHub. 1). Furthermore, the warning is not be printed when the home directory is not on NFS but Hi @stas00, Thanks for raising this interesting question. Init in the snippet below is offloaded to disk. DeepSpeed MII stable diffusion inference acceleration for single GPU; huggingface accelerate using DeepSpeed with various models for single GPU, current focus is diffusers and transformers with stable diffusion for training dreambooth, textual inversion, etc. For more information about Ascend, see Ascend Community. Deepspeed、LLM、Medical_Dialogue、医疗大模型、预训练、微调. Faster than zero/zero++/fsdp. 12. 4. I am using this codebase. distributed. AI-powered developer llama2 finetuning with deepspeed and lora. For detailed description about design principles, implementation, and performance evaluation against state-of-the-art checkpointing engines, please refer our HPDC'24 After cloning the DeepSpeed repo from GitHub, you can install DeepSpeed in JIT mode via pip (see below). Ongoing research training transformer language models at scale, including: BERT & GPT-2 - microsoft/Megatron-DeepSpeed Hi @tjruwase,. ai or the Github repo to learn more about the system innovations, publications, and people behind DeepSpeed. This library is not intended to be an independent user package, but is open-source to benefit the community and show how DeepSpeed is accelerating text-generation. So short term my usage is twofold. nlp bloom pipeline pytorch llama deepspeed llm #create python environment conda create -n DeepSpeed python=3. the scenario i'm thinking of is if i initialize ema_model and keep it on cpu, after i call deepspeed. . but it not work, Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Automate any workflow Codespaces Describe the bug Installing the latest Deepspeed is throwing error, we previously had 0. Describe the bug deepspeed. However, the training hagns during the 1st e "Star" our DeepSpeed GitHub and DeepSpeed-MII GitHub and DeepSpeedExamples GitHub repositories if you like our work! 6. Only happens with some of the models i've trained To follow up on this issue: the root cause is on the pytorch side. More than 100 million people use GitHub to discover, fork, Sample codes and guidelines on how to finetune any opensource GPT models using #deepspeed and #huggingface. 0+ (Ampere+), CUDA GitHub is where people build software. Find and fix vulnerabilities Actions. comm. AI-powered developer @szhengac, this issue is due to the fact that activation checkpointing causes backward hook to be invoked on each gradient of a shared weight, whereas without activation checkpointing backward hook is only However, deepspeed prints this warning even when TRITON_CACHE_DIR is set. Details can be found in the examples_deepspeed/rebase folder. and links to the deepspeed topic page so that developers can more easily learn about it. py --deepspeed --cai-chat --model pygmalion-6b Learn more For more information, check out this comment by 81300, who came up with the deepspeed support in this web UI. For installs spanning multiple nodes we find it useful to install DeepSpeed using the install. The DeepSpeed Autotuner mitigates this pain point and automatically discovers the optimal DeepSpeed configuration that delivers good training speed. Ongoing research training transformer language models at scale, including: BERT & GPT-2 - microsoft/Megatron-DeepSpeed MiniGPT-4基于DeepSpeed加速 扩充模型规模 实验分析. This installation should complete quickly since it is not compiling any C++/CUDA source files. 4 ninja py-cpuinfo libaio pydantic ca-certificates certifi openssl # install build tools pip install packaging build wheel setuptools loguru # DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. Megatron-DeepSpeed implements 3D Parallelism to allow huge models to train in a very efficient way. You can find examples here, and here. These buffers should DeepSpeed-Kernels is a backend library that is used to power DeepSpeed-FastGen to achieve accelerated text-generation inference through DeepSpeed-MII. gpt hf finetuning deepspeed llm Updated Mar 31, 2023; janelu9 / EasyLLM Star 0. Thanks for replying!!! I indeed am using deepspeed in pipeline mode. We will describe this through an example in How to use sparse attention with DeepSpeed launcher section. This repository contains various examples of using DeepSpeed, a Learn how to install and use DeepSpeed, a library for accelerating PyTorch models on various platforms. Pytorch Make sure you've read the DeepSpeed tutorials on Getting Started and Zero Redundancy Optimizer before stepping through this tutorial. I am trying to finetune Llama-3-8B with 2 A100 80GB for a few steps. AI-powered developer Hello, I want to perform inference on the HuggingFace MoE model Qwen1. DeepSpeed Stage 2 backward hook tracing with Compiled Autograd Accessing param. autograd hang until the end of the training step. These buffers should when I run build_win. Let’s briefly discuss the 3D components. Sign up for GitHub Background. So while yes, you can certainly, in theory, do fp16 math on CC 6. You are viewing main version, which requires installation from source. AI-powered developer DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. GitHub Gist: instantly share code, notes, and snippets. params. Assignees No one assigned Labels bug Something isn't working Ongoing research training transformer language models at scale, including: BERT & GPT-2 - microsoft/Megatron-DeepSpeed Please describe. 1 70b for 2 node, each node with 2 gpu, Sign up for a free GitHub account to open an issue and contact its maintainers and the community. You signed out in another tab or window. Describe the bug Hi, import torch from deepspeed. Sign up for a free GitHub account to open an issue and contact I set deepspeed --master_port 29600 main. We want to enable DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. AI-powered developer Describe the bug @exnx discovered that using larger gradient_accumulation_steps sizes with GPT-NeoX causes a large memory increase from smaller GAS sizes. 0. Visit deepspeed. barrier() doesn't have a timeout arg, so your deepspeed. We also thank the open-source library aspuru-guzik-group/qtorch. compile and facing multiple issues with respect to tracing the hooks. 4 with the OpenChat trainer, where checkpointing failed and raised an NCCL error. @Quentin-Anthony you were the last one to touch this line. The easiest way to use SA is through DeepSpeed launcher. One pain point in model training is to figure out good performance-relevant configurations such as micro-batch size to fully utilize the hardware and achieve a high throughput number. Automate any workflow Codespaces DeepSpeed brings together innovations in parallelism technology such as tensor, pipeline, expert and ZeRO-parallelism, and combines them with high performance custom inference kernels, communication optimizations and heterogeneous memory technologies to enable inference at an unprecedented scale, while achieving unparalleled latency, throughput and cost reduction. We are having a bit of hard time getting total_num_steps to pass to WarmupDecayLR at init time - it's a bit too early for the logic as these points are configured once ddp/ds has started - we found a workaround, but it doesn't take into the account the number of gpus. For ease of use and significant reduction in lengthy compile times that many projects require in this space we distribute a pre-compiled python wheel covering the majority of our custom kernels through a new library called DeepSpeed-Kernels. It is an easy-to-use deep learning optimization software suite that powers unprecedented scale and speed DeepNVMe improves the performance and efficiency of I/O operations in Deep Learning applications through powerful optimizations built on Non-Volatile Memory Express DeepSpeed is a library that enables fast and efficient training of large-scale models on various hardware platforms. - GitHub - erew123/alltalk_tts: AllTalk is based You signed in with another tab or window. I tried the following values: reduce_bucket_size: 500_000_000 — converges poorly; reduce_bucket_size: 1_000_000_000 — converges sllightly better in the beginning, but then still worse than Zero Stage 1. i want to compute gradients on the input for explainability. I run a 7b LLM with seq-len=1536. 0 (Pascal) predates Tensor Cores (fp16 ops with fp32 accumulate). Init. However, the DeepSpeed brings together innovations in parallelism technology such as tensor, pipeline, expert and ZeRO-parallelism, and combines them with high performance custom inference kernels, communication optimizations and heterogeneous memory technologies to enable inference at an unprecedented scale, while achieving unparalleled latency, throughput and cost reduction. 7B with expert parallelism using DeepSpeed in a multi-GPU environment. rand(10)]) yields [WARNING] cpu_adam cuda is missing or is incompatible with installed DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. PreTrainedTokenizer, model: transforme DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. - DeepSpeed/examples/README. Describe the bug I launch deepspeed training for a 600M parameter diffusion model, and only vary reduce_bucket_size. However, the official tutorials are not comprehensive enough, and despite reviewing the I am looking into running DeepSpeed with torch. Already have an account? Sign in to comment. AI-powered developer Deepspeed integration with mmdetection3d. Testing Checks on a Pull Request. AI-powered developer Contribute to c00cjz00/deepspeed_code development by creating an account on GitHub. They accidentally shipped the nvcc with their conda package which breaks the toolchain. The deepspeed_bsz24_config. Contribute to HerbiHerb/LLM_DeepSpeedExamples development by creating an account on GitHub. Unluckily, I did not observe speed up of training. zero. x, there isn't really hardware support for it--it's only going to go 1/64 as fast as fp32 on a GP104 like the chip in your 1080Ti, and of course the bigger problem for DeepSpeed etc is that it's going to use different I am using DeepSpeed with Zero Optimization (Stage 2) to train a custom model on multiple GPUs. 17 gcc==11. It can also be used with 3rd Party software via JSON calls. ZeRO-Inference for low-budget throughput scenarios: based on zero stage 3 is enabled using deepspeed. Init leaks. Describe the bug I am trying to train Llama2-7B-fp16 using 4 V100. ` deepspeed_config_file `: path to the DeepSpeed config file in ` json ` format. Describe the bug Hi, I'm not sure if it's a bug, but I get this error: line 75, in __init__ raise ValueError("Type fp16 is not supported. ; reduce_bucket_size: GitHub is where people build software. Automate any workflow Codespaces deepspeed --num_gpus=1 server. DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective we require the feature author to record their GitHub username as a contact method for future questions/maintenance. Sign up for GitHub DeepSpeed brings together innovations in parallelism technology such as tensor, pipeline, expert and ZeRO-parallelism, and combines them with high performance custom inference kernels, communication optimizations and heterogeneous memory technologies to enable inference at an unprecedented scale, while achieving unparalleled latency, throughput and cost reduction. You signed in with another tab or window. When running the nvidia_run_squad_deepspeed. DeepSpeed-Chat. ` deepspeed_multinode_launcher `: DeepSpeed multi-node launcher to use. 5) Sign up for a free GitHub account to open an issue and contact its maintainers and the community. total_num_steps expects the total for the whole world and not per gpu. ValidationError: Sign up for a free GitHub account to open an issue and contact its maintainers and DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. On the left is a DeepSpeed-VisualChat model, featuring an innovative attention design. The DeepSpeed source code is licensed under MIT License and DeepSpeed is a software suite for extreme speed and scale for DL training and inference. But before that, we introduce modules provided by DeepSpeed SA in the next section. py \ Sign up for free to join this conversation on GitHub. Click here for detailed tutorial on usage. initialize(). This issue aims to track the progress, bugs, and requests regarding the support of torch. 10x Faster Training. Navigation Menu Toggle navigation. Additional context Add any other context about the problem here. With increasing interest in enabling the multi-modal capabilities of large language models, DeepSpeed is proud to announce a new training pipeline Describe the bug @exnx discovered that using larger gradient_accumulation_steps sizes with GPT-NeoX causes a large memory increase from smaller GAS sizes. We are using DeepSpeed; transformer, accelerate to fine tune Qwen llm, and hit the below issue. Download them locally and follow the instructions below to run the training. If unspecified, will default to ` pdsh `. By comparing deepspeed stage-2 with native torch DDP (both fp32 training), I also encountered a similar problem, I think there must be some gap in the smoothing strategy between DS stage-2 and DDP thus leading to different DeepSpeed-Kernels is a backend library that is used to power DeepSpeed-FastGen to achieve accelerated text-generation inference through DeepSpeed-MII. monitored_barrier() call dropped the timeout arg. We highly recommend to install the teacher and student weights locally, therefore to not have to Describe the bug I am trying to run the non-persistent example given for mistralai/Mistral-7B-Instruct-v0. 12 openmpi numpy=1. xnkcpt iapqv dkpak lpoxme mpgq xhbghyv woia pfz wkmnmqhi lklvhg