Model Overview

The yibba/Atlas-Empathy-Darija is a 9 billion parameter language model, finetuned by yibba from the MBZUAI-Paris/Atlas-Chat-9B base model. This model was developed with a focus on efficient training, utilizing Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.

Key Characteristics

• Parameter Count: 9 billion parameters, offering a balance between performance and computational requirements.
• Context Length: Supports a context window of 16384 tokens, suitable for processing longer inputs and generating more coherent responses.
• Training Efficiency: Benefits from Unsloth's optimizations, leading to significantly faster finetuning.
• License: Released under the Apache-2.0 license, allowing for broad use and distribution.

Potential Use Cases

• Applications requiring a moderately sized, instruction-tuned model.
• Scenarios where efficient training and deployment are critical.
• Tasks benefiting from a 16K context window.