exploring-AI-optimization
nebuly
| exploring-AI-optimization | nebuly | |
|---|---|---|
| 22 | 105 | |
| 109 | 8,363 | |
| 0.0% | 0.1% | |
| 3.8 | 8.4 | |
| 7 months ago | 7 months ago | |
| Python | ||
| MIT License | Apache License 2.0 |
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exploring-AI-optimization
- Collection of material on optimizing deep learning models
- Collection of material on optimization techniques for neural networks
- Collection of resources on quantization
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[P] Open source that takes as input a deep learning model and outputs a version that runs faster in inference. Now faster and easier to use (New release)
[1] Quantization. Techniques and Concept Map. [2] Pruning. Techniques and Concept Map. [3] ONNX Runtime [4] Nvidia TensorRT [5] Intel OpenVINO [6] Apache TVM
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Accelerating AI models online discussion
https://github.com/nebuly-ai/learning-AI-optimization/blob/main/Pruning.md here you have open source collection of material on the topic :)
- What is pruning a neural network? A guide on github. Feedback is welcome!
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[P] Concept maps and research material on artificial intelligence optimization techniques (pruning and quantization). A guide on GitHub
Quantization github maps
nebuly
- Nebuly – The LLM Analytics Platform
- Ask HN: Any tools or frameworks to monitor the usage of OpenAI API keys?
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What are you building with LLMs? I'm writing an article about what people are building with LLMs
Hi everyone. I’m the creator of ChatLLaMA https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/chatllama, an opensource framework to train LLMs with limited resources and create There’s been amazing usage of LLMs in these days, from chatbots to retrieve about company’s product information, to cooking assistants for traditional dishes, and much more. And you? What you building or would love to build with LLMs? Let me know and I’ll share the article about your stories soon. https://qpvirevo4tz.typeform.com/to/T3PruEuE Cheers
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Show HN: ChatLLaMA – A ChatGPT style chatbot for Facebook's LLaMA
How does it differentiate from the original ChatLLaMA? https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...
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🤖🌟 Unlock the Power of Personal AI: Introducing ChatLLaMA, Your Custom Personal Assistant! 🚀💬
Was this made with the ChatLLaMA library? https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/chatllama
- Meta LLM LLaMA leaked, all over the internet as we speak
- Meta LLM LLAMA leaked, it's all over the internet as we speak.
- Meta LLM LLAMMA leaked, it's all over the internet as we speak.
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Plug and play modules to optimize the performances of your AI systems
Some of the available modules include:
Speedster: Automatically apply the best set of SOTA optimization techniques to achieve the maximum inference speed-up on your hardware. https://github.com/nebuly-ai/nebullvm/blob/main/apps/acceler...
Nos: Automatically maximize the utilization of GPU resources in a Kubernetes cluster through real-time dynamic partitioning and elastic quotas. https://github.com/nebuly-ai/nos
ChatLLaMA: Build faster and cheaper ChatGPT-like training process based on LLaMA architectures. https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...
OpenAlphaTensor: Increase the computational performances of an AI model with custom-generated matrix multiplication algorithm fine-tuned for your specific hardware. https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...
Forward-Forward: The Forward Forward algorithm is a method for training deep neural networks that replaces the backpropagation forward and backward passes with two forward passes. https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...
- Open source implementation for LLaMA-based ChatGPT
What are some alternatives?
best_AI_papers_2022 - A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
awesome-ai - A curated list of artificial intelligence resources (Courses, Tools, App, Open Source Project)
AITemplate - AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
prunnable-layers-pytorch - Prunable nn layers for pytorch.
alpaca-lora - Instruct-tune LLaMA on consumer hardware
Data-science-best-resources - Carefully curated resource links for data science in one place
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
openvino - OpenVINOâ„¢ is an open-source toolkit for optimizing and deploying AI inference