c1241fes/qwen-indonesian-sft-best
TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 14, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The c1241fes/qwen-indonesian-sft-best is a 7.6 billion parameter Qwen2.5 model, developed by c1241fes, specifically fine-tuned for Indonesian language tasks. This model leverages Unsloth and Huggingface's TRL library for accelerated training, offering a 32768 token context length. It is optimized for applications requiring strong performance in Indonesian language understanding and generation.
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Model Overview
The c1241fes/qwen-indonesian-sft-best is a 7.6 billion parameter language model based on the Qwen2.5 architecture, developed by c1241fes. It was fine-tuned from unsloth/qwen2.5-7b-unsloth-bnb-4bit with a focus on Indonesian language capabilities.
Key Characteristics
- Architecture: Qwen2.5 base model.
- Parameter Count: 7.6 billion parameters.
- Context Length: Supports a context window of 32768 tokens.
- Training Efficiency: Utilizes Unsloth and Huggingface's TRL library, resulting in a 2x faster fine-tuning process.
- Language Focus: Specifically fine-tuned for Indonesian language tasks, indicating enhanced performance for applications in this domain.
Intended Use Cases
This model is particularly well-suited for:
- Indonesian Language Processing: Applications requiring robust understanding and generation in Indonesian.
- Resource-Efficient Deployment: Benefits from the Unsloth optimization, potentially allowing for more efficient deployment compared to models trained without such acceleration.