krishmittal1/vedaz-astrologer-qwen2.5-7b-merged

TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jul 2, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The krishmittal1/vedaz-astrologer-qwen2.5-7b-merged is a 7.6 billion parameter Qwen2.5 model, finetuned by krishmittal1. This model was optimized for faster training using Unsloth and Huggingface's TRL library, making it efficient for specific instruction-following tasks. Its architecture is based on Qwen2.5, providing a robust foundation for various natural language processing applications.

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Model Overview

The krishmittal1/vedaz-astrologer-qwen2.5-7b-merged is a finetuned language model based on the Qwen2.5 architecture, developed by krishmittal1. This model has approximately 7.6 billion parameters and was specifically optimized for training efficiency.

Key Characteristics

  • Base Model: Finetuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit, indicating its foundation in the Qwen2.5 family.
  • Training Optimization: The model was trained significantly faster using Unsloth and Huggingface's TRL library. This suggests an emphasis on efficient resource utilization during the finetuning process.
  • License: Distributed under the Apache-2.0 license, allowing for broad usage and modification.

Potential Use Cases

Given its finetuned nature and the base model's instruction-following capabilities, this model is likely suitable for:

  • Specialized Instruction Following: Tasks requiring the model to adhere to specific instructions, potentially in a domain-specific context.
  • Efficient Deployment: Models trained with Unsloth are often optimized for reduced memory footprint and faster inference, making them suitable for environments with limited resources.
  • Further Finetuning: As a merged and finetuned model, it could serve as a strong base for additional domain-specific adaptations.