TirzYesLimit/qwen2.5-3b-alpaca-id
TEXT GENERATIONConcurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jun 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
TirzYesLimit/qwen2.5-3b-alpaca-id is a 3.1 billion parameter Qwen2.5-based causal language model developed by TirzYesLimit. Finetuned from unsloth/Qwen2.5-3B-Instruct-bnb-4bit, this model was trained using Unsloth and Huggingface's TRL library, enabling faster training. It features a 32768 token context length and is optimized for specific instruction-following tasks.
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TirzYesLimit/qwen2.5-3b-alpaca-id Overview
This model, developed by TirzYesLimit, is a 3.1 billion parameter instruction-tuned language model. It is finetuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model, leveraging the Qwen2.5 architecture. A key characteristic of its development is the use of Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
Key Capabilities
- Instruction Following: As an instruction-tuned model, it is designed to respond effectively to prompts and commands.
- Efficient Training: Benefits from optimization techniques provided by Unsloth, leading to quicker fine-tuning.
- Qwen2.5 Architecture: Inherits the robust capabilities of the Qwen2.5 model family.
Good For
- Applications requiring a compact yet capable instruction-following model.
- Scenarios where rapid deployment and efficient fine-tuning are beneficial.
- Tasks that can leverage a 3.1 billion parameter model with a 32768 token context length.