Search Results for "tuning"
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Showing 93 open source projects for "tuning"
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1
Llama Stack
Composable building blocks to build Llama Apps
Llama-Stack is an open-source framework designed to facilitate the deployment and fine-tuning of large language models (LLMs) for various natural language processing tasks. -
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NGINX Admin’s Handbook
How to improve NGINX performance, security, and other important things
...It distills years of research, notes, and field experience into a single handbook that complements the official docs with concrete rules, explanations, and curated external references. The handbook spans fundamentals and advanced topics alike, from HTTP and SSL/TLS basics to reverse proxy patterns, performance tuning, debugging workflows, and hardening strategies. A centerpiece is its prioritized checklist of 79 rules, grouped by criticality, helping readers focus on what most impacts security, reliability, and speed. Instead of copy-paste snippets in isolation, it emphasizes understanding trade-offs, avoiding common pitfalls, and balancing security with usability. ... -
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BayesianOptimization
A Python implementation of global optimization with gaussian processes
BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes. -
4
Unsloth-MLX
Bringing the Unsloth experience to Mac users via Apple's MLX framework
...It supports loading and training Hugging Face models with fine-tuning strategies like SFT, DPO, ORPO, and GRPO and even handles exporting models to formats like GGUF for downstream use, although some limitations apply with quantized models. Users can write and test training pipelines directly on macOS before scaling up, accelerating development cycles and lowering entry barriers for model refinement. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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5
Synthetic Data Kit
Tool for generating high quality Synthetic datasets
Synthetic Data Kit is a CLI-centric toolkit for generating high-quality synthetic datasets to fine-tune Llama models, with an emphasis on producing reasoning traces and QA pairs that line up with modern instruction-tuning formats. It ships an opinionated, modular workflow that covers ingesting heterogeneous sources (documents, transcripts), prompting models to create labeled examples, and exporting to fine-tuning schemas with minimal glue code. The kit’s design goal is to shorten the “data prep” bottleneck by turning dataset creation into a repeatable pipeline rather than ad-hoc notebooks. ... -
6
Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. -
7
JavaCore
JavaCore is a summary of experience with Java core technologies
...Its concurrency coverage includes threads, locks, atomics, thread pools, concurrent containers, synchronization, and the Java Memory Model. JVM chapters address memory, garbage collection, bytecode, class loading, diagnostics, monitoring, and performance tuning. -
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AUTOMATIC1111 Stable Diffusion web UI
Stable Diffusion web UI
AUTOMATIC1111's stable-diffusion-webui is a powerful, user-friendly web interface built on the Gradio library that allows users to easily interact with Stable Diffusion models for AI-powered image generation. Supporting both text-to-image (txt2img) and image-to-image (img2img) generation, this open-source UI offers a rich feature set including inpainting, outpainting, attention control, and multiple advanced upscaling options. With a flexible installation process across Windows, Linux, and... -
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OpenAI Cookbook
Examples and guides for using the OpenAI API
openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages. The repository is kept up to date and often expanded, and its examples are intended to serve both beginners and intermediate users of the API. ... -
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10
LLM Datasets
Curated list of datasets and tools for post-training
...The repository aims to make datasets easy to inspect and transform, with scripts for downloading, deduping, cleaning, and converting to formats like JSONL that slot into training pipelines. It highlights instruction-tuning and conversation-style corpora while also pointing to code, math, or domain-specific sets for targeted capabilities. Quality is a recurring theme: examples and utilities help filter low-value samples, enforce length limits, and split train/validation consistently so results are comparable. Licensing and provenance are surfaced to encourage compliant usage and to guide dataset selection in commercial settings. ... -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. ... -
12
ants
ants is a high-performance and low-cost goroutine pool in Go
...Managing and recycling a massive number of goroutines automatically. Purging overdue goroutines periodically. Abundant APIs: submitting tasks, getting the number of running goroutines, tuning capacity of pool dynamically, releasing pool, rebooting pool. Handle panic gracefully to prevent programs from crash. Efficient in memory usage and it even achieves higher performance than unlimited goroutines in Golang. Nonblocking mechanism. Just take a imagination that your program starts a massive number of goroutines, resulting in a huge consumption of memory. ... -
13
MLJ
A Julia machine learning framework
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization. -
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WebP Codec
Library to encode and decode images in WebP format
libwebp is the reference codec library for Google’s WebP image format, providing both encoding and decoding along with command-line tools. It supplies cwebp to compress images into WebP and dwebp to decompress them back, making it easy to test quality/size trade-offs across presets and tuning parameters. The GitHub repository is a mirror; the canonical source of truth lives on Chromium’s git, and developer docs are hosted on WebP’s portal. The project underpins WebP support across browsers, imaging libraries, and many native apps thanks to its stable C API. Additional companion repos host test data and demos, including JavaScript builds and timing tests for various platforms. ... -
15
Windows 11 Guide
Windows Security tools, Encryption, Nextcloud, Graphics, Gaming
Windows 11 Guide is a comprehensive, single-repository handbook for setting up and tuning a Windows 11 (and often Windows 10) desktop for real day-to-day use, covering everything from basic configuration to advanced development and gaming scenarios. It walks users through installing essential applications, configuring Windows security tools, setting up encryption and backups, and integrating productivity services like Nextcloud. -
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Index Advisor
PostgreSQL Index Advisor
index_advisor is a PostgreSQL extension developed by Supabase that suggests index optimizations based on query performance. It passively monitors query patterns and recommends indexes to improve performance without requiring deep database expertise. This tool helps developers and DBAs reduce query latency and improve efficiency in production environments. -
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StabilityMatrix
Multi-Platform Package Manager for Stable Diffusion
...This approach is useful for model selection, prompt engineering, and benchmarking new checkpoints against baseline models under reproducible conditions. By turning ad-hoc tests into tracked experiments, StabilityMatrix reduces bias, surfaces subtle regressions, and accelerates iteration when tuning generative systems. -
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Symfony WebProfilerBundle
Gives detailed information about the execution of any request
The Symfony Web Profiler Bundle is a powerful debugging and profiling tool that provides detailed insights into the internals of a Symfony application. It adds a web-based debug toolbar and an in-depth profiler that tracks HTTP requests, database queries, logs, events, and more. It is essential for performance tuning, debugging, and understanding application behavior during development. -
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Symfony DebugBundle
Provides a tight integration of the Symfony VarDumper component
...The bundle integrates deeply with Symfony’s profiler, offering insights into routing, database queries, and service usage, making it essential for debugging and performance tuning during development. -
20
glMatrix
Javascript Matrix and Vector library for High Performance WebGL apps
...These types of applications demand high performance vector and matrix math, which is something that Javascript doesn't provide by default. glMatrix to the rescue! glMatrix is designed to perform vector and matrix operations stupidly fast! By hand-tuning each function for maximum performance and encouraging efficient usage patterns through API conventions, glMatrix will help you get the most out of your browsers Javascript engine. -
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Cthulhu.jl
The slow descent into madness
Cthulhu.jl is a powerful introspection tool for exploring the Julia compiler’s method dispatch and type inference system. It allows users to interactively descend into the type-inferred lowered and LLVM IR of Julia functions from the REPL. This makes it ideal for developers who want to optimize performance, debug type instability, or understand how Julia compiles code. Named after the Lovecraftian idea of descending into madness, Cthulhu reveals the "underworld" of Julia compilation. -
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Backtrack Sampler
An easy-to-understand framework for LLM samplers
...It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs. -
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HumanSystemOptimization
Healthy Learning to 150 - An Incomplete Guide to Human System Tuning
HumanSystemOptimization is a long-form personal guide about health, learning, productivity, and daily habits rather than a software application. It summarizes ideas the author gathered from neuroscience podcasts, research discussions, and personal experimentation. Major sections discuss sleep, circadian rhythms, diet, exercise, focus, mood, learning, and other aspects of everyday performance. The repository mixes background explanations with practical routines and links to outside material... -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,... -
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OpenAI PHP Client
OpenAI PHP is a supercharged community-maintained PHP API client
The openai-php/client library is a PHP client for interacting with OpenAI’s API, enabling developers to integrate OpenAI models into their PHP applications. It simplifies sending API requests to access language models, generating text, processing natural language, and utilizing OpenAI’s advanced features. The library is designed to be easy to use, allowing developers to quickly set up and use OpenAI’s capabilities within their PHP projects.
