30 open-source projects similar to hc-guo/owl, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best HC Guo Owl alternative.
MOSS is a conversational AI platform, fine-tuning toolkit, and quantized model runtime. It provides a framework for deploying large language models capable of multi-turn dialogue, general-purpose response generation, and following complex instructions. The system functions as a tool-augmented framework that extends model knowledge through external plugins and tool-call loops. This allows the model to execute tasks via search engines and calculators to augment responses with external data. The project covers model training through supervised conversational fine-tuning and optimizes deployment
This project is a CJK input method framework and configuration set designed for the Rime input engine. It provides a comprehensive system of schemas and dictionary packs to optimize Chinese character entry through pinyin and double-pinyin workflows. The framework is distinguished by its use of Lua-powered extensions that add dynamic utilities, such as inline mathematical calculators, automated timestamps, and text formatting, directly to the input interface. It also features refined word libraries and language models specifically tuned to improve prediction accuracy and first-choice hit rates
An Instruction-tuned Large Language Model for E-commerce
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RWKV-LM is a framework for training and deploying recurrent language models. It utilizes a linear-time recurrent architecture that enables text generation and sequence processing with constant memory and time complexity, avoiding the quadratic scaling of traditional attention caches. The project implements a parallelizable training mechanism that allows recurrent models to be trained using global operations while maintaining cache-free inference. It includes state-tuning capabilities to optimize the initial hidden state and utilizes adaptive probability-mass sampling to control token diversit
CBLUE1 中文医疗信息处理基准CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
Industrial-first evaluation benchmark for LLMs in the DevOps/AIOps domain.
DevOps-Models is a series of industrial-first LLMs for theDevOps domain. Asking it for any question in the DevOps domain to get solution!
Dolly is an instruction-tuned large language model designed to follow complex natural language directions. It operates as a causal language model that predicts the next token in a sequence to generate coherent conversational responses and perform tasks such as brainstorming, classification, and question answering. The project focuses on the development of models using open datasets suitable for commercial application. It enables the creation of instruction-following models by utilizing curated collections of human-generated instruction-response pairs. The repository provides capabilities for
Code and datasets for paper "K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization" in WSDM-2024
DeepSeek-LLM is a large language model and causal language model designed for natural language generation. It functions as a multi-lingual system capable of predicting the next token in a sequence to perform text completion and conversational generation. The model is specialized for logical reasoning, specifically as a code and math LLM. This enables it to perform complex problem solving, which includes generating executable code and solving mathematical equations through step-by-step analysis. The system's broader capabilities cover conversational AI, including the generation of chat comple
An open-source educational chat model from ICALK, East China Normal University. 开源中英教育对话大模型。(通用基座模型,GPU部署,数据清理) 致敬: LLaMA, MOSS, BELLE, Ziya, vLLM
This repository is for EleutherAI's project Pythia which combines interpretability analysis and scaling laws to understand how knowledge develops and evolves during training in autoregressive transformers. For detailed info on the models, their training, and their properties, please see our…
Llama is a large language model runtime and inference engine designed to load and execute autoregressive transformer models. It enables the generation of natural language text completions from prompts using pretrained weights. The system features multi-GPU model parallelism, which distributes model weights and workloads across multiple graphics processors to support larger parameter counts. It also incorporates a content safety filter that uses classifiers to intercept and block unsafe inputs or outputs during the inference process. The project covers broad capabilities in distributed model
A large-scale language model for scientific domain, trained on redpajama arXiv split
This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum computing, and large-scale scientific data analysis. It provides foundational frameworks for developing complex algorithmic systems, offering the necessary infrastructure for distributed training, computational graph execution, and high-performance model development. The project distinguishes itself by integrating specialized research domains with robust, privacy-preserving methodologies. It supports diverse scientific discovery through tools for quantum simulation, physics-informed
Go to T5X ReadTheDocs Documentation Page.
This is a machine learning framework for treating diverse natural language processing tasks as a unified text-to-text problem. It provides a toolkit for pre-training and fine-tuning large-scale transformer models, utilizing a system where both inputs and outputs are formatted as raw text sequences. The framework is distinguished by its distributed training system, which uses mesh-based strategies to scale model weights and training batches across multiple TPU cores. It supports multi-task learning by combining diverse datasets into a single training stream using configurable mixture rates, al
h2oGPT is a self-hosted platform designed for running large language models and executing retrieval-augmented generation workflows locally. It provides a comprehensive web interface that allows users to index private document collections into searchable databases, enabling context-aware question answering and summarization without exposing sensitive data to external services. The platform distinguishes itself by offering a modular architecture that supports both local model execution and connections to external inference servers. It facilitates the development of autonomous agents capable of
CMMLU: Measuring massive multitask language understanding in Chinese
An open science effort to benchmark legal reasoning in foundation models