Showing 200 open source projects for "tuning"

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  • 1
    AMD APU Tuning Utility

    AMD APU Tuning Utility

    Unlock the full potential of your Zen-based APU with AMD APU Tuning

    Universal x86 Tuning Utility is a powerful tool designed to assist users in optimizing the performance and settings of their x86 laptops and computers. Its primary objective is to provide users with the ability to customize and fine-tune their device settings according to their preferences and needs. The development of this utility is spearheaded by the same talented team that brought us popular applications like Ryzen Controller, Renoir Mobile Tuning, and Power Control Panel. Universal x86...
    Downloads: 12 This Week
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  • 2
    LLaMA Efficient Tuning

    LLaMA Efficient Tuning

    Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon

    Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM2)
    Downloads: 0 This Week
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  • 3
    Intelligent Java

    Intelligent Java

    Integrate with the latest language models, image generation and speech

    ... results without tuning. Generate text; Cohere allows you to generate a language model to suit your specific needs. Generate audio from text; Access DeepMind’s speech models. The only dependencies is GSON. Required to add manually when using IntelliJava jar. However, if you imported this repo through Maven, it will handle the dependencies.
    Downloads: 12 This Week
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  • 4
    LLaVA

    LLaVA

    Visual Instruction Tuning: Large Language-and-Vision Assistant

    Visual instruction tuning towards large language and vision models with GPT-4 level capabilities.
    Downloads: 5 This Week
    Last Update:
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  • 5
    DeepFaceLive

    DeepFaceLive

    Real-time face swap for PC streaming or video calls

    You can swap your face from a webcam or the face in the video using trained face models. There is also a Face Animator module in DeepFaceLive app. You can control a static face picture using video or your own face from the camera. The quality is not the best, and requires fine face matching and tuning parameters for every face pair, but enough for funny videos and memes or real-time streaming at 25 fps using 35 TFLOPS GPU.
    Downloads: 221 This Week
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  • 6
    Neural Network Intelligence

    Neural Network Intelligence

    AutoML toolkit for automate machine learning lifecycle

    Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments...
    Downloads: 5 This Week
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  • 7
    promptfoo

    promptfoo

    Evaluate and compare LLM outputs, catch regressions, improve prompts

    Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API.
    Downloads: 5 This Week
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  • 8
    Alpaca.cpp

    Alpaca.cpp

    Locally run an Instruction-Tuned Chat-Style LLM

    Run a fast ChatGPT-like model locally on your device. This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint...
    Downloads: 8 This Week
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  • 9
    H2O LLM Studio

    H2O LLM Studio

    Framework and no-code GUI for fine-tuning LLMs

    Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell. With H2O LLM Studio, training your large language model is easy and intuitive. First, upload your dataset and then start...
    Downloads: 5 This Week
    Last Update:
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  • 10
    PEFT

    PEFT

    State-of-the-art Parameter-Efficient Fine-Tuning

    Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters. Fine-tuning large-scale PLMs is often prohibitively costly. In this regard, PEFT methods only fine-tune a small number of (extra) model parameters, thereby greatly decreasing the computational and storage costs. Recent State-of-the-Art PEFT techniques achieve performance comparable to that of full fine...
    Downloads: 0 This Week
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  • 11
    Envoy

    Envoy

    Cloud-native high-performance edge/middle/service proxy

    ... the network by providing common features in a platform-agnostic manner. With Envoy, visualizing problem areas becomes a lot easier thanks to consistent observability. It also helps with overall performance tuning, and easily adding substrate features in one place.
    Downloads: 5 This Week
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  • 12
    ModelScope

    ModelScope

    Bring the notion of Model-as-a-Service to life

    ... unified experience to explore state-of-the-art models spanning across domains such as CV, NLP, Speech, Multi-Modality, and Scientific-computation. Model contributors of different areas can integrate models into the ModelScope ecosystem through the layered APIs, allowing easy and unified access to their models. Once integrated, model inference, fine-tuning, and evaluations can be done with only a few lines of code.
    Downloads: 4 This Week
    Last Update:
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  • 13
    Anime Player

    Anime Player

    Video player for improving quality of hand-drawn images

    ... config for watching videos using the Anime4K algorithm on Android, viewing help and information about tuning the algorithm. The player also has support for frame interpolation using SVP. You need to install SVP and VapourSynth to work.
    Downloads: 5 This Week
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  • 14
    MedicalGPT

    MedicalGPT

    MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training

    MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training.
    Downloads: 1 This Week
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  • 15
    xTuring

    xTuring

    Easily build, customize and control your own LLMs

    xTuring is an open-source AI personalization software. xTuring makes it easy to build and control LLMs by providing a simple interface to personalize LLMs to your own data and application. xTuring provides fast, efficient and simple fine-tuning of LLMs, such as LLaMA, GPT-J, Galactica, and more. By providing an easy-to-use interface for fine-tuning LLMs to your own data and application, xTuring makes it simple to build, customize and control LLMs. The entire process can be done inside your...
    Downloads: 1 This Week
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  • 16
    Llama Recipes

    Llama Recipes

    Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT method

    The 'llama-recipes' repository is a companion to the Meta Llama models. We support the latest version, Llama 3.1, in this repository. The goal is to provide a scalable library for fine-tuning Meta Llama models, along with some example scripts and notebooks to quickly get started with using the models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama and other tools in the LLM ecosystem. The examples here showcase how to run...
    Downloads: 1 This Week
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  • 17
    Ultralight

    Ultralight

    Lightweight, high-performance HTML renderer for game developers

    ... for peak performance, ensuring minimal CPU and memory usage. Customize low-level platform functionality, integrate JavaScript directly with native code, dive deep into performance tuning, and more. Built for maximum portability, optimized for PCs, game consoles, TVs, and embedded systems.
    Downloads: 4 This Week
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  • 18
    Faiss

    Faiss

    Library for efficient similarity search and clustering dense vectors

    Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes...
    Downloads: 3 This Week
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  • 19
    MLE-Agent

    MLE-Agent

    Intelligent companion for seamless AI engineering and research

    MLE-Agent is designed as a pairing LLM agent for machine learning engineers and researchers. A library designed for managing machine learning experiments, tracking metrics, and model deployment.
    Downloads: 1 This Week
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  • 20
    Chronos Forecasting

    Chronos Forecasting

    Pretrained (Language) Models for Probabilistic Time Series Forecasting

    Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as...
    Downloads: 2 This Week
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  • 21
    Finetuner

    Finetuner

    Task-oriented finetuning for better embeddings on neural search

    Fine-tuning is an effective way to improve performance on neural search tasks. However, setting up and performing fine-tuning can be very time-consuming and resource-intensive. Jina AI’s Finetuner makes fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure in the cloud. With Finetuner, you can easily enhance the performance of pre-trained models, making them production-ready without extensive labeling or expensive hardware. Create high...
    Downloads: 0 This Week
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  • 22
    NGBoost

    NGBoost

    Natural Gradient Boosting for Probabilistic Prediction

    ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn and is designed to be scalable and modular with respect to the choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck.
    Downloads: 1 This Week
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  • 23
    Ludwig AI

    Ludwig AI

    Low-code framework for building custom LLMs, neural networks

    ...), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. Think building blocks for deep learning.
    Downloads: 1 This Week
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  • 24
    Ray

    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. Accelerate your hyperparameter search workloads with Ray Tune. Find the best...
    Downloads: 1 This Week
    Last Update:
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  • 25
    SetFit

    SetFit

    Efficient few-shot learning with Sentence Transformers

    SetFit is an efficient and prompt-free framework for few-shot fine-tuning of Sentence Transformers. It achieves high accuracy with little labeled data - for instance, with only 8 labeled examples per class on the Customer Reviews sentiment dataset, SetFit is competitive with fine-tuning RoBERTa Large on the full training set of 3k examples.
    Downloads: 0 This Week
    Last Update:
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