caffeinejunkie1/Qwen3-4B-Indo-Alpaca

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jun 14, 2026Architecture:Transformer0.0K Featherless Exclusive Cold

caffeinejunkie1/Qwen3-4B-Indo-Alpaca is a 4 billion parameter instruction-tuned causal language model developed by caffeinejunkie1. Built on the Qwen3-4B base, it is fine-tuned using Supervised Fine-Tuning (SFT) on a translated Indonesian Alpaca-GPT4 dataset. This model is specifically optimized for Indonesian natural language processing tasks, including text generation, question answering, and instruction-following, with a context length of 32768 tokens.

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Model Overview

caffeinejunkie1/Qwen3-4B-Indo-Alpaca is a 4 billion parameter instruction-tuned causal language model, developed by caffeinejunkie1. It is built upon the Qwen3-4B base model and has been fine-tuned using Supervised Fine-Tuning (SFT) on a high-quality, translated Indonesian Alpaca-GPT4 dataset. This model is primarily designed to understand and respond to instructions in Indonesian, making it a specialized tool for Indonesian NLP applications.

Key Capabilities

  • Indonesian Language Processing: Optimized for tasks in Indonesian, including text generation, summarization, and question answering.
  • Instruction Following: Fine-tuned to accurately follow instructions provided in Indonesian.
  • Conversational AI: Capable of assisting with general conversational tasks.
  • Base Model: Leverages the Qwen3-4B architecture, providing a robust foundation.
  • Context Length: Supports a context length of 32768 tokens.

Training Details

The model was exclusively fine-tuned on the Ichsan2895/alpaca-gpt4-indonesian dataset. This dataset consists of instruction-response pairs originally generated by GPT-4 and subsequently translated into Indonesian, ensuring high-quality training data for instruction-following capabilities.

Intended Use Cases

This model is ideal for:

  • Indonesian text generation.
  • Question answering in Indonesian.
  • Summarization of Indonesian content.
  • General instruction-following tasks in Indonesian.

It is not recommended for advanced mathematical reasoning, highly specialized medical or legal advice, or tasks requiring up-to-the-minute real-world knowledge due to its training data cutoff.

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