atzuke/DeepSeek-R1-Weather-control-v2-COT

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Apr 7, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

The atzuke/DeepSeek-R1-Weather-control-v2-COT is an 8 billion parameter Llama-based language model developed by atzuke. This model was fine-tuned from unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for specific applications, likely involving weather control or related reasoning tasks, given its name and fine-tuning origin.

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Model Overview

The atzuke/DeepSeek-R1-Weather-control-v2-COT is an 8 billion parameter language model developed by atzuke. It is based on the Llama architecture and was fine-tuned from the unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit model.

Key Characteristics

  • Architecture: Llama-based, specifically fine-tuned from a DeepSeek-R1 distilled variant.
  • Parameter Count: 8 billion parameters.
  • Training Efficiency: The model was trained with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • License: Released under the Apache-2.0 license.

Potential Use Cases

Given its name, "Weather-control-v2-COT," this model is likely specialized for tasks related to:

  • Complex reasoning (Chain-of-Thought, COT) in specific domains.
  • Applications involving weather data analysis, prediction, or simulated control scenarios.
  • Research and development in specialized AI applications requiring efficient fine-tuning on Llama-based models.