Search Results for "research" - Page 5
Sort By:
Showing 112 open source projects for "research"
View related business solutions-
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
-
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
1
Alpaca-CoT
We unified the interfaces of instruction-tuning data
Alpaca-CoT is an open research project focused on improving reasoning capabilities in language models through chain-of-thought training data. The project builds upon the Alpaca instruction-tuning approach by introducing datasets and methods that encourage models to produce intermediate reasoning steps when solving problems. Instead of generating answers directly, the model learns to produce logical reasoning sequences that lead to the final solution. -
2
DB-GPT-Hub
A repository that contains models, datasets, and fine-tuning
DB-GPT-Hub is an open-source repository that provides datasets, models, and training tools designed to improve large language models for database interaction tasks, particularly Text-to-SQL. The project serves as a specialized extension of the broader DB-GPT ecosystem, focusing on the preparation and evaluation of models capable of translating natural language questions into structured database queries. It offers a modular framework that supports data preparation, model fine-tuning,... -
3
Autolabel
Label, clean and enrich text datasets with LLMs
Autolabel is a Python library to label, clean and enrich datasets with Large Language Models (LLMs). Autolabel data for NLP tasks such as classification, question-answering and named entity recognition, entity matching and more. Seamlessly use commercial and open-source LLMs from providers such as OpenAI, Anthropic, HuggingFace, Google and more. -
4
ReplitLM
Inference code and configs for the ReplitLM model family
...These models are designed specifically for coding workflows and are trained on large datasets of source code covering many programming languages and development environments. The repository also includes documentation and tutorials for integrating the models into development tools, APIs, or research pipelines. Developers can fine-tune the models using instruction-tuning techniques to adapt them for specific programming tasks or domains. The models were trained using modern deep learning techniques and large-scale GPU infrastructure to achieve strong performance in code completion and generation tasks. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
5
LLaMA
Inference code for Llama models
“Llama” is the repository from Meta (formerly Facebook/Meta Research) containing the inference code for LLaMA (Large Language Model Meta AI) models. It provides utilities to load pre-trained LLaMA model weights, run inference (text generation, chat, completions), and work with tokenizers. Tokenizer utilities, download scripts, shell helpers to fetch model weights with correct licensing/permissions. -
6
ReAct Prompting
Synergizing Reasoning and Acting in Language Models
ReAct is an open-source research project that demonstrates a prompting and reasoning framework designed to improve the problem-solving capabilities of large language models. The project implements the methodology described in the research paper “ReAct: Synergizing Reasoning and Acting in Language Models,” which combines reasoning traces with action-based interactions. -
7
ThoughtSource
A central, open resource for data and tools
ThoughtSource is a central, open resource and community centered on data and tools for chain-of-thought reasoning in large language models (Wei 2022). Our long-term goal is to enable trustworthy and robust reasoning in advanced AI systems for driving scientific research and medical practice. -
8
Chinese-LLaMA-Alpaca-2 v2.0
Chinese LLaMA & Alpaca large language model + local CPU/GPU training
This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which significantly improves the model's ability to understand and execute instructions. -
9
unit-minions
AI R&D Efficiency Improvement Research: Do-It-Yourself Training LoRA
"AI R&D Efficiency Improvement Research: Do-It-Yourself Training LoRA", including Llama (Alpaca LoRA) model, ChatGLM (ChatGLM Tuning) related Lora training. Training content: user story generation, test code generation, code-assisted generation, text to SQL, text generation code. -
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.
-
10
GPT-NeoX
Implementation of model parallel autoregressive transformers on GPUs
...Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we recommend Mesh Transformer JAX. If you are not looking to train models with billions of parameters from scratch, this is likely the wrong library to use. For generic inference needs, we recommend you use the Hugging Face transformers library instead which supports GPT-NeoX models. -
11
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. -
12
Grade School Math
8.5K high quality grade school math problems
...The problems are written by human authors (not automatically generated) to ensure linguistic variety and realism. The repository maintains strict formatting (e.g. JSONL) for problem + answer pairs, and is used broadly in research to benchmark model performance under “word problem” settings. Issues are tracked (people report incorrect problems, ambiguous statements), and contributions are possible for cleaning or expanding the set.
