Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) InstructProtein - AWQ - Model creator: https://huggingface.co/hicai-zju/ - Original model: https://huggingface.co/hicai-zju/InstructProtein/ Original model description: --- license: mit --- # InstructProtein InstructProtein is the first large generative language model exploring the feasibility of bidirectional generation between human and protein language. It is based on OPT-1.3B architecture with two-step training approach: It initiates with pre-training on protein and natural language corpora, followed by fine-tuning with the established protein knowledge instruction dataset. Through further instruction tuning, InstructProtein outperforms larger general-purpose foundation models on protein understanding and design tasks. ## Limitations The current model, developed through instruction tuning using knowledge instruction dataset, serves as a preliminary example. Despite its initial success in controlled environments, it lacks the robustness to manage complex, real-world, production-level tasks. ## Reference For more information, please take a look at our [paper](https://arxiv.org/abs/2310.03269) and [repository](https://github.com/HICAI-ZJU/InstructProtein).