ishala/qwen3-8b-instruct-indo-grpo
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 18, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The ishala/qwen3-8b-instruct-indo-grpo is an 8 billion parameter instruction-tuned Qwen3 model developed by ishala, finetuned from ishala/qwen3-8b-instruct-indo-sft. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general instruction-following tasks, leveraging its optimized training process for efficient performance.
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ishala/qwen3-8b-instruct-indo-grpo: An Optimized Qwen3 Model
This model, developed by ishala, is an 8 billion parameter instruction-tuned variant of the Qwen3 architecture. It was finetuned from the ishala/qwen3-8b-instruct-indo-sft model, indicating a focus on instruction-following capabilities.
Key Characteristics
- Architecture: Based on the Qwen3 model family.
- Parameter Count: Features 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Optimization: A notable aspect of this model is its training methodology. It was trained 2x faster using Unsloth in conjunction with Huggingface's TRL library. This suggests an emphasis on efficient model development and deployment.
- Context Length: Supports a substantial context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Use Cases
Given its instruction-tuned nature and optimized training, this model is well-suited for:
- General instruction-following tasks.
- Applications requiring efficient inference from an 8B parameter model.
- Scenarios where faster training and iteration cycles are beneficial.