zpqrs/qwen-analyst-16bit
TEXT GENERATIONConcurrency Cost:1Model Size:14.8BQuant:FP8Ctx Length:32kPublished:Feb 19, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The zpqrs/qwen-analyst-16bit is a 14.8 billion parameter Qwen2 model developed by zpqrs, fine-tuned from unsloth/qwen2.5-14b-instruct-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. With a 32768 token context length, it is optimized for analytical tasks and efficient processing.
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Model Overview
The zpqrs/qwen-analyst-16bit is a 14.8 billion parameter Qwen2 model, developed by zpqrs. It is fine-tuned from the unsloth/qwen2.5-14b-instruct-bnb-4bit base model, leveraging the Qwen2.5 architecture.
Key Characteristics
- Efficient Training: This model was trained with Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Parameter Count: Features 14.8 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a substantial context window of 32768 tokens, suitable for processing longer inputs and maintaining conversational coherence over extended interactions.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Good For
- Analytical Tasks: The fine-tuning process and base model choice suggest suitability for tasks requiring detailed analysis and instruction following.
- Applications requiring efficient models: Its optimized training indicates potential for deployment in environments where resource efficiency is a consideration.
- Extended Context Processing: The large context window makes it well-suited for applications that involve processing and understanding lengthy documents or complex conversations.