EasyLM
LLM framework
A framework for training and serving large language models using JAX/Flax
Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
2k stars
43 watching
258 forks
Language: Python
last commit: 6 months ago
Linked from 1 awesome list
chatbotdeep-learningflaxjaxlanguage-modellarge-language-modelsllamanatural-language-processingtransformer
Related projects:
Repository | Description | Stars |
---|---|---|
| An open-source toolkit for pretraining and fine-tuning large language models | 2,732 |
| A comprehensive course and resource package on building and deploying Large Language Models (LLMs) | 40,053 |
| A curated collection of high-quality datasets for training large language models. | 2,708 |
| A Python-based framework for serving large language models with low latency and high scalability. | 2,691 |
| A curated list of resources to help developers navigate the landscape of large language models and their applications in NLP | 9,551 |
| A framework for efficient fine-tuning and deployment of large language models | 4,659 |
| An implementation of a method for fine-tuning language models to follow instructions with high efficiency and accuracy | 5,775 |
| A general-purpose language model pre-trained with an autoregressive blank-filling objective and designed for various natural language understanding and generation tasks. | 3,207 |
| An efficient C#/.NET library for running Large Language Models (LLMs) on local devices | 2,750 |
| Developing and pretraining a GPT-like Large Language Model from scratch | 35,405 |
| Compiles and organizes key papers on pre-trained language models, providing a resource for developers and researchers. | 3,331 |
| A fast serving framework for large language models and vision language models. | 6,551 |
| Provides a unified framework to test generative language models on various evaluation tasks. | 7,200 |
| A tool for efficiently fine-tuning large language models across multiple architectures and methods. | 36,219 |
| An implementation of a large language model using the nanoGPT architecture | 6,013 |