adhistya/Qwen2.5-Trading-Architect-Merged
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Dec 12, 2025License:apache-2.0Architecture:Transformer Open Weights Cold
The adhistya/Qwen2.5-Trading-Architect-Merged is a 7.6 billion parameter Qwen2.5 model developed by adhistya, fine-tuned from unsloth/qwen2.5-7b-instruct-bnb-4bit. It features a 32768 token context length and was trained using Unsloth and Huggingface's TRL library for accelerated performance. This model is specialized for applications requiring a Qwen2.5 base with optimized training efficiency.
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adhistya/Qwen2.5-Trading-Architect-Merged Overview
This model is a 7.6 billion parameter Qwen2.5 variant, developed by adhistya and fine-tuned from the unsloth/qwen2.5-7b-instruct-bnb-4bit base. It leverages a substantial 32768 token context window, making it suitable for processing extensive inputs.
Key Capabilities
- Efficient Training: The model was trained with Unsloth and Huggingface's TRL library, enabling a 2x faster fine-tuning process compared to standard methods.
- Qwen2.5 Architecture: Benefits from the robust capabilities of the Qwen2.5 instruction-tuned base model.
- Large Context Window: Supports a 32768 token context, allowing for detailed analysis and generation over long sequences of text.
Good For
- Developers seeking a Qwen2.5-based model with optimized training efficiency.
- Applications requiring a large context window for complex tasks.
- Use cases where rapid fine-tuning and deployment are critical.