Search Results for "gpt" - Page 6
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Showing 148 open source projects for "gpt"
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ImPromptu
Domain Agnostic Prompts for Savvy Professionals
A community-driven wiki of sorts full of your favorite prompts for various Large Language Models such as ChatGPT, GPT-3, MidJourney, and soon (Google's Bard) and more! Choose a subject area you are interested in, and click the link below to go to the page with prompts for that subject. If that page is empty, then you can help by adding prompts to that page. If you are not sure how to do that, you can read the contributing guidelines. If you are feeling like having your mind melt into magic today then head over to the prompt generator and let the magic happen. ... -
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OpenDelta
A plug-and-play library for parameter-efficient-tuning
OpenDelta is an open-source parameter-efficient fine-tuning library that enables efficient adaptation of large-scale pre-trained models using delta tuning techniques. OpenDelta is a toolkit for parameter-efficient tuning methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most parameters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning... -
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AI Chatbots based on GPT Architecture
Training & Implementation of chatbots leveraging GPT-like architecture
Training & Implementation of chatbots leveraging GPT-like architecture with the aitextgen package to enable dynamic conversations. It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose) by training a text-generation model to generate conversation in a consistent structure. ... -
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DialoGPT
Large-scale pretraining for dialogue
DialoGPT is an open-source conversational language model developed by Microsoft Research for generating natural dialogue responses using large-scale transformer architectures. The system is built on the GPT-2 architecture and is designed specifically for multi-turn conversation tasks, enabling machines to produce coherent responses during interactive dialogue. The model was trained on a massive dataset of approximately 147 million conversational exchanges extracted from Reddit discussion threads, allowing it to learn patterns of natural human conversation. ... -
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KoboldAI
Your gateway to GPT writing
This is a browser-based front-end for AI-assisted writing with multiple local & remote AI models. It offers the standard array of tools, including Memory, Author's Note, World Info, Save & Load, adjustable AI settings, formatting options, and the ability to import existing AI Dungeon adventures. You can also turn on Adventure mode and play the game like AI Dungeon Unleashed. Stories can be played like a Novel, a text adventure game or used as a chatbot with an easy toggles to change... -
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LaMDA-pytorch
Open-source pre-training implementation of Google's LaMDA in PyTorch
Open-source pre-training implementation of Google's LaMDA research paper in PyTorch. The totally not sentient AI. This repository will cover the 2B parameter implementation of the pre-training architecture as that is likely what most can afford to train. You can review Google's latest blog post from 2022 which details LaMDA here. You can also view their previous blog post from 2021 on the model. -
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AI Atelier
Based on the Disco Diffusion, version of the AI art creation software
Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. When a modified version is used to provide a service over a network, the complete source code of the modified version must be made available. ... -
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PromptSource
Toolkit for creating, sharing and using natural language prompts
PromptSource is a toolkit for creating, sharing and using natural language prompts. Recent work has shown that large language models exhibit the ability to perform reasonable zero-shot generalization to new tasks. For instance, GPT-3 demonstrated that large language models have strong zero- and few-shot abilities. FLAN and T0 then demonstrated that pre-trained language models fine-tuned in a massively multitask fashion yield even stronger zero-shot performance. A common denominator in these works is the use of prompts which has gained interest among NLP researchers and engineers. ... -
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GPT Neo
An implementation of model parallel GPT-2 and GPT-3-style models
...Training and inference is officially supported on TPU and should work on GPU as well. This repository will be (mostly) archived as we move focus to our GPU-specific repo, GPT-NeoX. NB, while neo can technically run a training step at 200B+ parameters, it is very inefficient at those scales. This, as well as the fact that many GPUs became available to us, among other things, prompted us to move development over to GPT-NeoX. All evaluations were done using our evaluation harness. Some results for GPT-2 and GPT-3 are inconsistent with the values reported in the respective papers. ... -
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gpt-2-simple
Python package to easily retrain OpenAI's GPT-2 text-generating model
...If you are training in the cloud, using a Colaboratory notebook or a Google Compute Engine VM w/ the TensorFlow Deep Learning image is strongly recommended. (as the GPT-2 model is hosted on GCP) You can use gpt-2-simple to retrain a model using a GPU for free in this Colaboratory notebook, which also demos additional features of the package. Note: Development on gpt-2-simple has mostly been superceded by aitextgen, which has similar AI text generation capabilities with more efficient training time. -
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KoGPT
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
KoGPT is a Korean language model based on OpenAI’s GPT architecture, designed for various natural language processing (NLP) tasks such as text generation, summarization, and dialogue systems. -
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gpt-j-api
API for the GPT-J language mode. Including a FastAPI backend
An API to interact with the GPT-J language model and variants! You can use and test the model in two different ways. These are the endpoints of the public API and require no authentication. Just SSH into a TPU VM. This code was tested on both the v2-8 and v3-8 variants. -
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Rescatux
Easy to use Repair distribution for both Gnu/Linux and Windows systems
Rescatux is a GNU/Linux repair cd (and eventually also Windows) but it is not like other rescue disks. Rescatux comes with Rescapp. Rescapp is a nice wizard that will guide you through your rescue and repair tasks. When the wizard is not able to solve your problem you can also enjoy of Rescatux unique support features: * Chat: Open the chat for asking help directly in Rescatux channel. * Share log: After running an option you can share its log (the action registry that it has done) so... -
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hebrew-gpt_neo
Hebrew text generation models based on EleutherAI's gpt-neo
Hebrew text generation models based on EleutherAI's gpt-neo. Each was trained on a TPUv3-8 which was made available to me via the TPU Research Cloud Program. The Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the goclassy architecture. -
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Image GPT
Large-scale autoregressive pixel model for image generation by OpenAI
Image-GPT is the official research code and models from OpenAI’s paper Generative Pretraining from Pixels. The project adapts GPT-2 to the image domain, showing that the same transformer architecture can model sequences of pixels without altering its fundamental structure. It provides scripts to download pretrained checkpoints of different model sizes (small, medium, large) trained on large-scale datasets and includes utilities for handling color quantization with a 9-bit palette. ... -
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CRSLab
CRSLab is an open-source toolkit
...Comprehensive benchmark models and datasets: We have integrated commonly-used 6 datasets and 18 models, including graph neural network and pre-training models such as R-GCN, BERT and GPT-2. We have preprocessed these datasets to support these models, and release for downloading. Extensive and standard evaluation protocols: We support a series of widely-adopted evaluation protocols for testing and comparing different CRS. General and extensible structure: We design a general and extensible structure to unify various conversational recommendation datasets and models, in which we integrate various built-in interfaces and functions for quickly development. ... -
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Tabnine
Vim client for TabNine
Tabnine is an AI-powered code completion extension trusted by millions of developers around the world. Whether you’re just getting started as a developer or if you’ve been doing it for decades, Tabnine will help you code twice as fast with half the keystrokes – all in your favorite IDE. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or... -
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TensorFlow 2.0 Tutorials
TensorFlow 2.x version's Tutorials and Examples
...These examples cover a wide range of topics including convolutional neural networks, recurrent neural networks, generative adversarial networks, autoencoders, and transformer-based models such as GPT and BERT. Each section of the repository includes runnable code and structured experiments designed to illustrate how different architectures and algorithms function in real applications. The tutorials use well-known benchmark datasets such as MNIST, CIFAR, and Fashion-MNIST to demonstrate practical model training and evaluation workflows. -
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GPT-2 FR
GPT-2 French demo | Démo française de GPT-2
OpenAI GPT-2 model trained on four different datasets in French. Books in French, French film scripts, reports of parliamentary debates, Tweet by Emmanuel Macron, allowing to generate text. Tensorflow and gpt-2-simple are required in order to fine-tune GPT-2. Create an environment then install the two packages pip install tensorflow==1.14 gpt-2-simple. -
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gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
GPT-2 is a Natural Language Processing model developed by OpenAI for text generation. It is the successor to the GPT (Generative Pre-trained Transformer) model trained on 40GB of text from the internet. It features a Transformer model that was brought to light by the Attention Is All You Need paper in 2017. The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. -
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gpt-oss-20b
OpenAI’s compact 20B open model for fast, agentic, and local use
...Like its larger sibling (gpt-oss-120b), it offers adjustable reasoning depth and full chain-of-thought visibility for better interpretability. It’s released under a permissive Apache 2.0 license, allowing unrestricted commercial and research use. GPT-OSS-20B is compatible with Transformers, vLLM, Ollama, PyTorch, and other tools. It is ideal for developers building lightweight AI agents or experimenting with fine-tuning on consumer-grade hardware. -
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DeepSeek-V3.2-Speciale
High-compute ultra-reasoning model surpassing model surpassing GPT-5
...Unlike the standard version, Speciale is tuned exclusively for deep reasoning and therefore does not support tool-calling, focusing its full capacity on pure cognitive performance. The model uses a scaled reinforcement learning framework that allows it to surpass GPT-5 in several evaluations and reach reasoning performance comparable to Gemini-3.0-Pro. DeepSeek-V3.2-Speciale contributed to gold-medal solutions in the 2025 IMO, IOI, ICPC World Finals, and CMO, demonstrating its ability to handle elite-level problem solving. It is released under the MIT license and includes curated benchmark solutions for community verification and analysis. -
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DeepSeek-V3.2
High-efficiency reasoning and agentic intelligence model
...It introduces DeepSeek Sparse Attention (DSA), a new attention mechanism that dramatically reduces computational overhead while maintaining strong long-context performance. Built with a scalable reinforcement learning framework, it reaches near-GPT-5 levels of reasoning and outperforms comparable models like DeepSeek-V3.1 and Gemini-3.0-Pro in advanced benchmarks. The model was notably used in competitive AI challenges such as the 2025 International Mathematical Olympiad (IMO) and IOI, achieving top-tier results. DeepSeek-V3.2 also features a large-scale agentic task synthesis pipeline, which generates training data to enhance tool-use intelligence and multi-step reasoning. ...
