fakhrijongkeng12/Llama3.1-Indonesian-Fine-Tuned

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 29, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

fakhrijongkeng12/Llama3.1-Indonesian-Fine-Tuned is an 8 billion parameter Llama 3.1 model, fine-tuned specifically for Indonesian language tasks. Developed by fakhrijongkeng12, this model leverages Unsloth and Huggingface's TRL library for faster training. It is designed to provide enhanced performance and understanding for applications requiring Indonesian language processing, building upon the Llama 3.1 architecture.

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Llama3.1-Indonesian-Fine-Tuned Overview

This model, developed by fakhrijongkeng12, is an 8 billion parameter Llama 3.1 variant that has been fine-tuned for the Indonesian language. It was trained using Unsloth and Huggingface's TRL library, which enabled a 2x faster fine-tuning process compared to standard methods.

Key Characteristics

  • Base Model: Llama 3.1 architecture.
  • Parameter Count: 8 billion parameters.
  • Training Efficiency: Utilizes Unsloth for accelerated fine-tuning.
  • Language Focus: Specifically fine-tuned for Indonesian language understanding and generation.

Intended Use Cases

This model is particularly well-suited for applications requiring robust performance in Indonesian, such as:

  • Natural Language Understanding (NLU) in Indonesian.
  • Text generation in Indonesian.
  • Chatbots or conversational AI systems operating in Indonesian.
  • Content creation and summarization for Indonesian text.

Finetunes
1 models