wrapyfi-examples_llama
FlexGen
wrapyfi-examples_llama | FlexGen | |
---|---|---|
2 | 39 | |
128 | 9,035 | |
0.0% | 1.1% | |
4.0 | 3.5 | |
about 1 year ago | about 1 month ago | |
Python | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
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wrapyfi-examples_llama
- [D] Is it possible to run Meta's LLaMA 65B model on consumer-grade hardware?
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Wrapyfi for distributing LLaMA by Meta on different machines
The authors present an example of combining Wrapyfi (https://github.com/fabawi/wrapyfi), a Python wrapper for message-oriented and robotics middleware, with LLaMA (https://github.com/facebookresearch/llama), a series of large language models from Meta AI. They demonstrate how Wrapyfi can enable running LLaMA on multiple mid-range machines with high inference speed and low cost. They also provide links to their GitHub repository (https://github.com/modular-ml/wrapyfi-examples_llama) and paper (https://arxiv.org/abs/2302.09648) for more details. They state that this example can revolutionize natural language processing tasks such as text generation, summarization, question answering, sentiment analysis, etc. without having to buy new hardware and use their existing infrastructure!
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
What are some alternatives?
llama - Inference code for Llama models
llama-cpu - Fork of Facebooks LLaMa model to run on CPU
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
text-generation-inference - Large Language Model Text Generation Inference
text-g
whisper.cpp - Port of OpenAI's Whisper model in C/C++
llama-int8 - Quantized inference code for LLaMA models
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
audiolm-pytorch - Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch
minimal-llama