DeepSpeed VS fairscale

Compare DeepSpeed vs fairscale and see what are their differences.

DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. (by microsoft)

fairscale

PyTorch extensions for high performance and large scale training. (by facebookresearch)
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DeepSpeed fairscale
42 6
25,390 2,333
7.9% 3.4%
9.6 4.9
4 days ago 18 days ago
Python Python
Apache License 2.0 GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

DeepSpeed

Posts with mentions or reviews of DeepSpeed. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-02.

fairscale

Posts with mentions or reviews of fairscale. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-27.

What are some alternatives?

When comparing DeepSpeed and fairscale you can also consider the following projects:

ColossalAI - Making large AI models cheaper, faster and more accessible

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.

Megatron-LM - Ongoing research training transformer models at scale

fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

mesh-transformer-jax - Model parallel transformers in JAX and Haiku

llama - Inference code for LLaMA models

gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.

server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.

Megatron-DeepSpeed - Ongoing research training transformer language models at scale, including: BERT & GPT-2

text-generation-webui - A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA.

Finetune_LLMs - Repo for fine-tuning GPTJ and other GPT models

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration