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README.md

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+Quantization made by Richard Erkhov.
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+[Github](https://github.com/RichardErkhov)
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+[Discord](https://discord.gg/pvy7H8DZMG)
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+[Request more models](https://github.com/RichardErkhov/quant_request)
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+
+InstructProtein - AWQ
+- Model creator: https://huggingface.co/hicai-zju/
+- Original model: https://huggingface.co/hicai-zju/InstructProtein/
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+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.
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+## Limitations
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+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.
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+## Reference
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+For more information, please take a look at our [paper](https://arxiv.org/abs/2310.03269) and [repository](https://github.com/HICAI-ZJU/InstructProtein).
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