Update README.md

README.md

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 This model was converted to GGUF format from [`SakanaAI/TAID-LLM-1.5B`](https://huggingface.co/SakanaAI/TAID-LLM-1.5B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/SakanaAI/TAID-LLM-1.5B) for more details on the model.
 
+---
+TAID-LLM-1.5B is an English language model created 
+through TAID (Temporally Adaptive Interpolated Distillation), our new 
+knowledge distillation method. 
+We used Qwen2-72B-Instruct as the teacher model and Qwen2-1.5B-Instruct as the student model. 
+
+
+
+	
+		
+	
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+		Model Details
+	
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+
+
+Developed by: Sakana AI
+Model type: Autoregressive Language Model
+Language(s): English
+License: Apache License, Version 2.0
+Paper: https://arxiv.org/abs/2501.16937
+Blog: https://sakana.ai/taid/
+
+
+
+	
+		
+	
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+		Uses
+	
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+This model is provided for research and development purposes only and
+ should be considered as an experimental prototype. 
+It is not intended for commercial use or deployment in mission-critical 
+environments. 
+Use of this model is at the user's own risk, and its performance and 
+outcomes are not guaranteed. 
+Sakana AI shall not be liable for any direct, indirect, special, 
+incidental, or consequential damages, or any loss arising from the use 
+of this model, regardless of the results obtained. 
+Users must fully understand the risks associated with the use of this 
+model and use it at their own discretion.
+
+
+
+	
+		
+	
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+		Acknowledgement
+	
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+
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+We would like to thank the developers of the source models for their contributions and for making their work available. 
+
+
+This model is based on results obtained from a project, JPNP20017, 
+subsidized by the New Energy and Industrial Technology Development 
+Organization (NEDO).
+
+
+
+	
+		
+	
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+		Citation
+	
+
+
+
+@misc{sakana2025taid,
+      title         = {TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models}, 
+      author.       = {Makoto Shing and Kou Misaki and Han Bao and Sho Yokoi and Takuya Akiba},
+      year          = {2025},
+      eprint        = {2501.16937},
+      archivePrefix = {arXiv},
+      primaryClass  = {cs.LG},
+      url           = {https://arxiv.org/abs/2501.16937}
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)