sikkaBolega/printfarm-sft-merged
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:Apr 25, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
sikkaBolega/printfarm-sft-merged is a 3.1 billion parameter Qwen2-based instruction-tuned language model developed by sikkaBolega. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its Qwen2 architecture for robust performance.
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Overview
sikkaBolega/printfarm-sft-merged is a 3.1 billion parameter instruction-tuned language model based on the Qwen2 architecture. Developed by sikkaBolega, this model was fine-tuned using the Unsloth library, which is known for accelerating the training process, and Huggingface's TRL library. This approach allowed for a significantly faster training time, specifically noted as 2x faster.
Key Capabilities
- Instruction Following: Optimized for understanding and executing a wide range of instructions.
- Efficient Training: Benefits from Unsloth's optimizations, leading to quicker fine-tuning cycles.
- Qwen2 Foundation: Leverages the robust capabilities of the Qwen2 base model.
Good For
- Applications requiring a compact yet capable instruction-tuned model.
- Scenarios where rapid deployment and efficient fine-tuning are priorities.
- General-purpose text generation and understanding tasks.