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DeepSpeed Alternatives
Similar projects and alternatives to DeepSpeed
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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gpt-neox
An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
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TensorRT
NVIDIA® TensorRT™, an SDK for high-performance deep learning inference, includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for inference applications.
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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server
The Triton Inference Server provides an optimized cloud and edge inferencing solution. (by triton-inference-server)
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Finetune_GPTNEO_GPTJ6B
Repo for fine-tuning GPTJ and other GPT models
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diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch (by ShivamShrirao)
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diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
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accelerate
🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
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XMem
[ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
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EfficientZero
Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.
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msn
Masked Siamese Networks for Label-Efficient Learning (https://arxiv.org/abs/2204.07141)
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CodeRL
This is the official code for the paper CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning (NeurIPS22).
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
DeepSpeed reviews and mentions
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39.7 it/s with a 4090 on Linux!
I tried installing PyTorch 2.0.0, with triton from here microsoft/DeepSpeed#2694, compiling my own xformers and it made my inference even slower. From 17-18it/s 512x512, Batch size: 1, any sampling method to around 16-17it/s but especially with Batch size: 8, from 5.65it/s to 4.66it/s.
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What does ACCELERATE do in AUTOMATIC1111?
To activate it you have to uncomment webui-user.sh line 44 and adding set ACCELERATE="True" to webui-user.bat. It seems to use huggingface/accelerate (Microsoft DeepSpeed, ZeRO paper) ACCELERATE
- New (simple) Dreambooth method is out, train under 10 minutes without class images on multiple subjects, retrainable-ish model
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[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
DeepSpeed Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale - Microsoft 2022 Paper: https://arxiv.org/pdf/2207.00032.pdf Github: https://github.com/microsoft/DeepSpeed
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[D] Does someone know how much faster deepspeed's transformer implementation is?
Implementation here
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Nvidia Fiscal Q3 2022 Financial Result
Described a collaboration involving NVIDIA Megatron-LM and Microsoft DeepSpeed to create an efficient, scalable, 3D parallel system capable of combining data, pipeline and tensor-slicing-based parallelism.
- [P] PyTorch-LIT - Infer Large Models That Don't Even Fit in Main Memory
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Microsoft and NVIDIA AI Introduces MT-NLG: The Largest and Most Powerful Monolithic Transformer Language NLP Model
Microsoft and NVIDIA present the Megatron-Turing Natural Language Generation model (MT-NLG), powered by DeepSpeed and Megatron, the largest and robust monolithic transformer language model trained with 530 billion parameters.
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How to Train Large Models on Many GPUs?
DeepSpeed [1] is amazing tool to enable the different kind of parallelisms and optimizations on your model. I would definitely not recommend reimplementing everything yourself.
Probably FairScale [2] too, but never tried it myself.
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A note from our sponsor - InfluxDB
www.influxdata.com | 29 Jan 2023
Stats
microsoft/DeepSpeed is an open source project licensed under MIT License which is an OSI approved license.