Fizzarolli/L3.1-70b-glitz-v0.2

Glitz v0.2: An Experimental L3.1 70B Model

Glitz v0.2 is an experimental 70 billion parameter L3.1 model, developed by Fizzarolli. This version represents a fine-tuning run that, despite crashing midway through, yielded interesting results worth publishing. The model was trained using a diverse dataset, primarily consisting of publicly available Claude synthetic data across various domains, alongside systemchat data.

Key Characteristics

• Architecture: Based on the L3.1 model family.
• Parameter Count: 70 billion parameters, offering significant capacity for complex language understanding and generation.
• Context Length: Supports a substantial 32768 token context window, enabling the processing of longer inputs and maintaining coherence over extended conversations or documents.
• Training Data: Fine-tuned on a blend of publicly available Claude synthetic data and systemchat, contributing to its general language capabilities.

Usage and Prompting

This model is designed to be used with L3 instruct prompting. While specific examples are not provided, the developer notes that most modern LLM interfaces support this prompting style.

Limitations

It is important to note that this model's training run was incomplete, which may influence its performance or introduce unexpected behaviors compared to fully trained models.