A unified interface for LLMs

OpenChat is a library of open-source language models, fine-tuned with "C-RLFT (Conditioned Reinforcement Learning Fine-Tuning)" - a strategy inspired by offline reinforcement learning. It has been trained on mixed-quality data without preference labels.

A #merge model based on Llama-2-13B and made possible thanks to the compute provided by the KoboldAI community. It's a merge between:

• KoboldAI/LLaMA2-13B-Tiefighter
• chaoyi-wu/MedLLaMA_13B
• Doctor-Shotgun/llama-2-13b-chat-limarp-v2-merged.

#merge

Anthropic's model for low-latency, high throughput text generation. Supports up to 100k tokens in one pass, or hundreds of pages of text.

A continuation of OpenHermes 2 model, trained on additional code datasets. Potentially the most interesting finding from training on a good ratio (est. of around 7-14% of the total dataset) of code instruction was that it has boosted several non-code benchmarks, including TruthfulQA, AGIEval, and GPT4All suite. It did however reduce BigBench benchmark score, but the net gain overall is significant.

This model offers four times the context length of gpt-3.5-turbo, allowing it to support approximately 20 pages of text in a single request at a higher cost. Training data: up to Sep 2021.