rieffs/pengenalan-emosi
TEXT GENERATIONConcurrency Cost:1Model Size:0.5BQuant:BF16Ctx Length:32kPublished:Mar 10, 2026Architecture:Transformer Warm
rieffs/pengenalan-emosi is a 0.5 billion parameter instruction-tuned model, converted to GGUF format and optimized using Unsloth. This model is designed for efficient deployment and inference on local hardware, supporting both text-only and multimodal applications. Its primary use case is for emotion recognition tasks, leveraging its compact size for faster processing.
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Overview
rieffs/pengenalan-emosi is a compact 0.5 billion parameter instruction-tuned model, specifically optimized and converted to the GGUF format using Unsloth. This optimization allows for significantly faster training and inference, making it suitable for efficient local deployment.
Key Capabilities
- Efficient Local Inference: Optimized GGUF format for smooth execution on consumer hardware.
- Instruction-Tuned: Designed to follow instructions for various tasks.
- Multimodal Support: Can be used with multimodal applications, in addition to text-only LLMs.
- Fast Training: Benefits from Unsloth's 2x faster training capabilities.
Good for
- Emotion Recognition: The model's name suggests a specialization in emotion recognition tasks.
- Edge Devices: Its small parameter count and GGUF format make it ideal for deployment on devices with limited resources.
- Rapid Prototyping: Fast training and easy deployment via Ollama facilitate quick experimentation and development.
- Local Development: An included Ollama Modelfile simplifies setup for local use.