Ahana05/qwen2.5-astrologer-model

TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 2, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Ahana05/qwen2.5-astrologer-model is a 7.6 billion parameter Qwen2.5-based causal language model developed by Ahana05. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its Qwen2.5 architecture for broad applicability.

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Model Overview

Ahana05/qwen2.5-astrologer-model is a 7.6 billion parameter language model built upon the Qwen2.5 architecture. Developed by Ahana05, this model was fine-tuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit.

Key Characteristics

  • Architecture: Based on the Qwen2.5 family of models.
  • Parameter Count: 7.6 billion parameters, offering a balance between performance and computational efficiency.
  • Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Context Length: Supports a context length of 32768 tokens.
  • License: Released under the Apache-2.0 license.

Intended Use Cases

This model is suitable for a variety of general instruction-following tasks, benefiting from its Qwen2.5 foundation and efficient fine-tuning. Its optimized training process suggests it could be a good candidate for applications requiring a capable language model with a focus on efficient development and deployment.