Dnoya10/dicoding_genAI_sft_eks2
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 14, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
Dnoya10/dicoding_genAI_sft_eks2 is a 1.5 billion parameter Qwen2-based instruction-tuned causal language model developed by Dnoya10. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology and a substantial 32768 token context length.
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Overview
Dnoya10/dicoding_genAI_sft_eks2 is a 1.5 billion parameter instruction-tuned language model based on the Qwen2 architecture. Developed by Dnoya10, this model was finetuned using the Unsloth library and Huggingface's TRL, which allowed for a significantly faster training process (2x faster).
Key Capabilities
- Instruction Following: Optimized for understanding and executing a wide range of instructions.
- Efficient Training: Benefits from Unsloth's optimizations for faster finetuning.
- Large Context Window: Features a 32768 token context length, suitable for processing longer inputs and generating coherent, extended responses.
Good For
- General Purpose AI Applications: Suitable for various tasks requiring instruction adherence and text generation.
- Resource-Efficient Deployment: Its 1.5 billion parameter size makes it a good candidate for applications where computational resources are a consideration, while still offering strong performance due to its Qwen2 base and optimized finetuning.
- Experimentation with Unsloth: Demonstrates the effectiveness of Unsloth for accelerating model finetuning.