FasterTransformer
Transformer related optimization, including BERT, GPT (by NVIDIA)
CodeGen
CodeGen is a family of open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex. (by salesforce)
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| FasterTransformer | CodeGen | |
|---|---|---|
| 7 | 18 | |
| 5,456 | 4,762 | |
| 4.2% | 1.5% | |
| 4.3 | 6.1 | |
| about 1 month ago | about 1 month ago | |
| C++ | Python | |
| Apache License 2.0 | Apache License 2.0 |
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.
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.
FasterTransformer
Posts with mentions or reviews of FasterTransformer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-08.
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Train Your AI Model Once and Deploy on Any Cloud
https://docs.nvidia.com/ai-enterprise/overview/0.1.0/platfor...
RIVA: NVIDIA® Riva, a premium edition of NVIDIA AI Enterprise software, is a GPU-accelerated speech and translation AI SDK
FasterTransformer: https://github.com/NVIDIA/FasterTransformer an
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Whether the ML computation engineering expertise will be valuable, is the question.
There could be some spectrum of this expertise. For instance, https://github.com/NVIDIA/FasterTransformer, https://github.com/microsoft/DeepSpeed
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Optimized implementation of training/fine-tuning of LLMs [D]
Have anyone tried to optimize the forward and backward using custom Cuda code or fused kernel to speed up the training time of current LLMs? I only have seen FasterTransformer ( NVIDIA/FasterTransformer) and other similar tools but they're only focusing on inference.
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Exploring Ghostwriter, a GitHub Copilot alternative
Replit built Ghostwriter on the open source scene based on Salesforce’s Codegen, using Nvidia’s FasterTransformer and Triton server for highly optimized decoders, and the knowledge distillation process of the CodeGen model from two billion parameters to a faster model of one billion parameters.
- Why are self attention not as deployment friendly?
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[P] What we learned by making T5-large 2X faster than Pytorch (and any autoregressive transformer)
Nvidia FasterTransformer is a mix of Pytorch and CUDA/C++ dedicated code. The performance boost is huge on T5, they report a 10X speedup like TensorRT. However, the speedup is computed on a translation task where sequences are 25 tokens long on average. In our experience, improvement on very short sequences tend to decrease by large margins on longer ones. Still we plan to dig deeper into this project as it implements very interesting ideas.
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[P] Python library to optimize Hugging Face transformer for inference: < 0.5 ms latency / 2850 infer/sec
On the other side of the spectrum, there is Nvidia demos (here or there) showing us how to build manually a full Transformer graph (operator by operator) in TensorRT to get best performance from their hardware. It’s out of reach for many NLP practitioners and it’s time consuming to debug/maintain/adapt to a slightly different architecture (I tried). Plus, there is a secret: the very optimized model only works for specific sequence lengths and batch sizes. Truth is that, so far (and it will improve soon), it’s mainly for MLPerf benchmark (the one used to compare DL hardware), marketing content, and very specialized engineers.
CodeGen
Posts with mentions or reviews of CodeGen.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-10-23.
- FLaNK Stack Weekly 23 Oct 2023
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Seeking Resources on Open-source Large Language Models Specializing in Causality Tasks
CodeGen (I included this model as there's some evidence in recent months that LLMs trained on code-related tasks better capture long-range dependencies compared to LLMs trained on 'just words')
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Free alternative to OpenAI Copilot
https://github.com/salesforce/CodeGen these are used in fauxpilot https://github.com/fauxpilot/fauxpilot
- FauxPilot – an open-source GitHub Copilot server
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GitHub Copilot X: The AI-powered developer experience
You can always use https://github.com/salesforce/CodeGen . But it does require managing the model hosting. You can use fauxpilot to mimic copilot functionality https://github.com/fauxpilot/fauxpilot
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Will we see a “stable diffusion” version of ChatGPT?
freediver 2 days ago | prev | next [–] Here is an example of one general purpose open source LLM, probably the best you can get: https://github.com/EleutherAI/gpt-neox To manage your expectations it is nowhere as good as ChatGPT. If you are interested in programming only: https://github.com/salesforce/CodeGen
- Codegen: Open-Source Codex Equivalent
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Exploring Ghostwriter, a GitHub Copilot alternative
Replit built Ghostwriter on the open source scene based on Salesforce’s Codegen, using Nvidia’s FasterTransformer and Triton server for highly optimized decoders, and the knowledge distillation process of the CodeGen model from two billion parameters to a faster model of one billion parameters.
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We've filed a lawsuit against GitHub Copilot
https://github.com/moyix/fauxpilot is working on an open source variant. Based on https://github.com/salesforce/CodeGen
- Open Source model to generate code competitive with OpenAI Codex/GitHub Copilot
What are some alternatives?
When comparing FasterTransformer and CodeGen you can also consider the following projects:
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
fauxpilot - FauxPilot - an open-source alternative to GitHub Copilot server
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
pifs - πfs - the data-free filesystem!
transformer-deploy - Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀
copilot
parallelformers - Parallelformers: An Efficient Model Parallelization Toolkit for Deployment
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.
wenet - Production First and Production Ready End-to-End Speech Recognition Toolkit
cformers - SoTA Transformers with C-backend for fast inference on your CPU.
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
NewtonianEotWashToolkit - A simple point-wise Newtonian gravitational force calculator
FasterTransformer vs TensorRT
CodeGen vs fauxpilot
FasterTransformer vs onnxruntime
CodeGen vs pifs
FasterTransformer vs transformer-deploy
CodeGen vs copilot
FasterTransformer vs parallelformers
CodeGen vs gpt-neox
FasterTransformer vs wenet
CodeGen vs cformers
FasterTransformer vs DeepSpeed
CodeGen vs NewtonianEotWashToolkit