PolyLM
Multilingual LLM
A polyglot large language model designed to address limitations in current LLM research and provide better multilingual instruction-following capability.
77 stars
1 watching
7 forks
Language: Python
last commit: over 1 year ago Related projects:
Repository | Description | Stars |
---|---|---|
| A benchmark for evaluating large language models in multiple languages and formats | 93 |
| A collection of information about various large language models used in natural language processing | 272 |
| A multi-modal large language model that integrates natural language and visual capabilities with fine-tuning for various tasks | 73 |
| A framework that enables large language models to process and understand multimodal inputs from various sources such as images and speech. | 308 |
| An open-source multilingual large language model designed to understand and generate content across diverse languages and cultural contexts | 92 |
| A multi-modal language model that integrates image, video, audio, and text data to improve language understanding and generation | 1,568 |
| An open bilingual LLM developed using the LingoWhale model, trained on a large dataset of high-quality middle English text, and fine-tuned for specific tasks such as conversation generation. | 134 |
| A large language model pre-trained on Chinese and English data, suitable for natural language processing tasks. | 43 |
| A lightweight, multilingual language model with a long context length | 920 |
| Large language models designed to perform well in multiple languages and address performance issues with current multilingual models. | 476 |
| An open-source implementation of a vision-language instructed large language model | 513 |
| A framework for training GPT4-style language models with multimodal inputs using large datasets and pre-trained models | 231 |
| An LLaMA-based multimodal language model with various instruction-following and multimodal variants. | 17 |
| A tool for training and fine-tuning large language models using advanced techniques | 387 |
| A framework for serving large language models with a robust and efficient API | 909 |