rahulchowdary07/qwen-astro-ft
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jul 2, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The rahulchowdary07/qwen-astro-ft is a 7.6 billion parameter Qwen2.5-Instruct model, fine-tuned by rahulchowdary07. This model was efficiently trained using Unsloth and Huggingface's TRL library, offering a 32768 token context length. It is optimized for faster training and deployment, making it suitable for applications requiring a capable Qwen2.5-based language model.
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Model Overview
The rahulchowdary07/qwen-astro-ft is a 7.6 billion parameter language model, fine-tuned by rahulchowdary07. It is based on the Qwen2.5-Instruct architecture and features a substantial context length of 32768 tokens.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen2.5-7B-Instruct-bnb-4bit. - Efficient Training: This model was trained with significant speed improvements, utilizing the Unsloth library in conjunction with Huggingface's TRL library. This approach allows for faster fine-tuning processes.
- Developer: Developed by rahulchowdary07.
- License: Distributed under the Apache-2.0 license.
Good For
- Rapid Prototyping: Its efficient training methodology makes it suitable for developers looking to quickly deploy and iterate on Qwen2.5-based applications.
- General Language Tasks: As an instruction-tuned model, it is well-suited for a wide range of natural language processing tasks, including text generation, summarization, and question answering.
- Applications requiring a Qwen2.5 variant: Users specifically seeking a fine-tuned version of Qwen2.5-7B-Instruct will find this model relevant.