Starling-7B

  • PROJECT DIRECT URL: Starling-7B Official Website
  • DESCRIPTION: Starling-7B, a project from UC Berkeley, stands out for its use of the Nectar dataset to achieve remarkable performance in MT Bench. It is designed to rival even the most advanced models like Claude 2 and Llama-2, proving the growing efficacy of open-source LLMs in achieving near or surpassing proprietary model performance levels.

DeepSeek 67B

  • PROJECT DIRECT URL: DeepSeek 67B on ar5iv
  • DESCRIPTION: DeepSeek 67B excels across various benchmarks, especially in code, mathematics, and reasoning, outperforming models like LLaMA-2 70B and GPT-3.5. It represents a significant leap in open-source LLM development, offering high-quality responses and engaging conversations in both Chinese and English, underscoring its global applicability and excellence.

Chameleon

  • PROJECT DIRECT URL: Chameleon on Github
  • DESCRIPTION: Chameleon is a novel compositional reasoning framework designed to augment large language models (LLMs) like GPT-4, enabling them to overcome some of their inherent limitations such as outdated information and lack of precise reasoning. It does this by integrating a variety of tools — including vision models, web search engines, Python functions, and rule-based modules — to provide more accurate, up-to-date, and precise responses. This makes Chameleon a significant innovation in the field of natural language processing, demonstrating substantial improvements in accuracy on benchmark tasks and setting new standards for the industry.

OpenLLM

  • PROJECT DIRECT URL: OpenLLM on GitHub
  • DESCRIPTION: OpenLLM is engineered for AI application developers focusing on building production-ready applications leveraging large language models. It provides an extensive toolkit for fine-tuning, serving, deploying, and monitoring LLMs, greatly simplifying the deployment workflow from end to end.

WizardCoder-15B

  • PROJECT DIRECT URL: WizardCoder-15B
  • DESCRIPTION: WizardCoder-15B is designed for coding tasks, excelling in understanding and generating code instructions accurately. Its foundation is built upon StarCoder, and it employs the Evol-Instruct method for specialized training, making it highly effective for code generation, understanding programming concepts, and debugging.

Stable Code 3B

  • PROJECT DIRECT URL: table Code 3B
  • DESCRIPTION: Stable Code 3B is a compact, high-performance LLM for code completion, developed by Stability AI. It stands out for its ability to operate offline on common laptops and its training on software engineering-specific data, offering advanced code completion across multiple programming languages.

OctoCoder

  • PROJECT DIRECT URL: Hugging Face - OctoCoder
  • DESCRIPTION: OctoCoder, with 15.5 billion parameters, is a versatile AI coding model proficient in over 80 programming languages. It is fine-tuned on unique datasets for a wide range of coding tasks, adaptable across various hardware setups.

Redmond-Hermes-Coder 15B

  • PROJECT DIRECT URL: Hugging Face - Redmond-Hermes-Coder 15B
  • DESCRIPTION: Redmond-Hermes-Coder 15B, developed by Nous Research in collaboration with various partners, represents the cutting-edge in code generation technology. It has been fine-tuned on a large dataset of instructions, outperforming predecessors in the domain of coding tasks. ndard in multilingual language model performance.

Code Llama (7B, 13B, 34B)

  • PROJECT DIRECT URL: Hugging Face - Code Llama
  • DESCRIPTION: Code Llama offers a trio of models for coding tasks, trained on a vast dataset of code. With variants designed for different scales and specialized versions for Python, these models are tailored for a wide range of coding requirements from code generation to immediate code completion.

T5

  • PROJECT DIRECT URL: T5 on TensorFlow
  • DESCRIPTION: The Text-to-Text Transfer Transformer (T5) continues to excel in the NLP space, offering versatility in translating text across various tasks. Its open-source framework allows for comprehensive customization and application in a wide range of language processing tasks.