FlexGen
audiolm-pytorch
| FlexGen | audiolm-pytorch | |
|---|---|---|
| 39 | 4 | |
| 9,007 | 2,249 | |
| 0.8% | - | |
| 3.0 | 9.0 | |
| 15 days ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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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.
FlexGen
- Run 70B LLM Inference on a Single 4GB GPU with This New Technique
- Colorful Custom RTX 4060 Ti GPU Clocks Outed, 8 GB VRAM Confirmed
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Local Alternatives of ChatGPT and Midjourney
LLaMA, Pythia, RWKV, Flan-T5 (self-hosted), FlexGen
- FlexGen: Running large language models on a single GPU
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Show HN: Finetune LLaMA-7B on commodity GPUs using your own text
> With no real knowledge of LLM and only recently started to understand what LLM terms mean, such as 'model, inference, LLM model, intruction set, fine tuning' whatelse do you think is required to make a took like yours?
This was mee a few weeks ago. I got interested in all this when FlexGen (https://github.com/FMInference/FlexGen) was announced, which allowed to run inference using OPT model on consumer hardware. I'm an avid user of Stable Diffusion, and I wanted to see if I can have an SD equivalent of ChatGPT.
Not understanding the details of hyperparameters or terminology, I basically asked ChatGPT to explain to me what these things are:
Explain to someone who is a software engineer with limited knowledge of ML terms or linear algebra, what is "feed forward" and "self-attention" in the context of ML and large language models. Provide examples when possible. - Could this new flexgen be used in place of GPTq? or is this different?
- OpenAI is expensive
audiolm-pytorch
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Bark: A transformer based text to audio system
It’s mostly there in https://github.com/lucidrains/audiolm-pytorch#hierarchical-t....
- FLiPN-FLaNK Stack Weekly 27Feb2023
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Implementation of Google's MusicLM in PyTorch
This one is AudioLM modified from here https://github.com/lucidrains/audiolm-pytorch repository to support the music generation needs here.
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Microsoft’s new text-to-speech model can duplicate anyone's voice in 3 seconds
There is an open source implementation of these features in Pytorch:
https://github.com/lucidrains/audiolm-pytorch
What are some alternatives?
llama - Inference code for Llama models
bark - 🔊 Text-Prompted Generative Audio Model
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
highlight - highlight.io: The open source, full-stack monitoring platform. Error monitoring, session replay, logging, distributed tracing, and more.
text-generation-inference - Large Language Model Text Generation Inference
musiclm-pytorch - Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch
whisper.cpp - Port of OpenAI's Whisper model in C/C++
iTransformer - Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
jxc - JXC is a structured data language similar to JSON, but with a focus on being expressive, extensible, and human-friendly.
minimal-llama
yobulkdev - 🔥 🔥 🔥Open Source & AI driven Data Onboarding Platform:Free flatfile.com alternative