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Nexus-IKM-Mistral-Instruct-v0.2-7B

@@ -8,7 +8,7 @@ pipeline_tag: text-generation
 <img src="https://cdn-uploads.huggingface.co/production/uploads/64740cf7485a7c8e1bd51ac9/GO4MY_3adP2G9EHKZbZpg.webp" width="500" height="500">
-# **ACCIDENTALLY PUSHED YHE WRONG VERSION, THIS ONE IS UNFORTUNATELY LOBOTOMIZED. FIXED VERSION UP TODAY. SORRY, I AM CONTINUOUSLY ITERATING ON THESE MODELS TO IMPROVE ON THEM**
 **This model is the Pytorch / Unsloth version trained on the experimental 'Internal Knowledge Map' dataset. The training was for 3 Epochs with the suggested settings.** Developed with an aim to go beyond the scope of usual data processing capabilities, this model gets trained to build comprehensive understanding and reasoning in a wide range of knowledge domains with elaborate guidelines. It bases its reasoning on a specially selected dataset emphasizing the interrelations of the diverse disciplines which aim to synthesize, integrate, and apply complex information in ways that mimic humanly abstract reasoning and creative thought processes.
 At the very core of the development of this model is the desire to make sure that LLMs engage in a kind of cognitive activity not limited to memory but actually taking on abstract reasoning, problem-solving, and generation of new insights. To achieve this, 'Nexus-IKM-Mistral-7B' has been fine-tuned until convergance using a novel Phased Training appraoch on this unique dataset, which resulted in the model demonstrating greater capability for giving rise to insights and problem-solving in complex, multi-disciplinary settings. This involves improved ability in drawing links between different pieces of knowledge, reasoning through complex scenarios, and proposing innovative solutions that cut across various domains, including science, technology, environmental studies, and humanities.

 <img src="https://cdn-uploads.huggingface.co/production/uploads/64740cf7485a7c8e1bd51ac9/GO4MY_3adP2G9EHKZbZpg.webp" width="500" height="500">
+# **ACCIDENTALLY PUSHED THE WRONG VERSION, THIS ONE IS UNFORTUNATELY LOBOTOMIZED. FIXED VERSION UP TODAY. SORRY, I AM CONTINUOUSLY ITERATING ON THESE MODELS TO IMPROVE ON THEM**
 **This model is the Pytorch / Unsloth version trained on the experimental 'Internal Knowledge Map' dataset. The training was for 3 Epochs with the suggested settings.** Developed with an aim to go beyond the scope of usual data processing capabilities, this model gets trained to build comprehensive understanding and reasoning in a wide range of knowledge domains with elaborate guidelines. It bases its reasoning on a specially selected dataset emphasizing the interrelations of the diverse disciplines which aim to synthesize, integrate, and apply complex information in ways that mimic humanly abstract reasoning and creative thought processes.
 At the very core of the development of this model is the desire to make sure that LLMs engage in a kind of cognitive activity not limited to memory but actually taking on abstract reasoning, problem-solving, and generation of new insights. To achieve this, 'Nexus-IKM-Mistral-7B' has been fine-tuned until convergance using a novel Phased Training appraoch on this unique dataset, which resulted in the model demonstrating greater capability for giving rise to insights and problem-solving in complex, multi-disciplinary settings. This involves improved ability in drawing links between different pieces of knowledge, reasoning through complex scenarios, and proposing innovative solutions that cut across various domains, including science, technology, environmental studies, and humanities.