| Property | Value |
|---|---|
| Base Model | meta-llama/Llama-3.1-70B-Instruct |
| License | MIT |
| Training Infrastructure | 8 x H100 SXM GPUs |
| Training Method | QLoRA Fine-tuning |
What is Cakrawala-Llama-3.1-70B?
Cakrawala-Llama-3.1-70B is a specialized language model fine-tuned for generating immersive roleplaying conversations. Built upon the Llama-3.1-70B-Instruct architecture, this model has been specifically optimized to excel at producing detailed character interactions with rich emotional depth and consistent personality traits.
Implementation Details
The model was trained using sophisticated technical parameters, including a learning rate of 0.0002, AdamW optimizer, and Cosine scheduler. It leverages mixed precision training with BF16 & FP16 with TF32 support, utilizing gradient accumulation steps of 1 and a micro batch size of 4.
- Training dataset: 13,000 conversation pairs with minimum 12-13 turns each
- Training duration: 2 epochs
- Optimization: QLoRA fine-tuning methodology
- Precision: Mixed precision implementation (BF16 & FP16)
Core Capabilities
- Rich character dialogue generation
- Detailed facial expression and environmental descriptions
- Consistent character voice maintenance
- Contextually appropriate emotional responses
- Extended interaction handling
Frequently Asked Questions
Q: What makes this model unique?
This model's uniqueness lies in its specialized training for roleplaying scenarios, with particular emphasis on maintaining character consistency and generating detailed environmental and emotional descriptions. The extensive training dataset of long-form conversations ensures high-quality, contextually rich interactions.
Q: What are the recommended use cases?
The model is specifically designed for roleplaying applications, character-based storytelling, and interactive narrative generation. It excels in scenarios requiring detailed character interactions, emotional depth, and consistent personality traits.