Hamanasu-Magnum-QwQ-32B
| Property | Value |
|---|---|
| Parameter Count | 32B |
| Base Model | Hamanasu-QwQ-V2-RP |
| Training Hardware | 8x H100s |
| Available Formats | GGUF (pending), EXL2 |
| Model URL | https://huggingface.co/Delta-Vector/Hamanasu-Magnum-QwQ-32B |
What is Hamanasu-Magnum-QwQ-32B?
Hamanasu-Magnum-QwQ-32B is a sophisticated language model fine-tuned to replicate the prose style of Claude models (Opus and Sonnet). The model represents a significant advancement in roleplay-oriented AI, trained specifically on high-quality conversational datasets including Claude instructions and various specialized corpora.
Implementation Details
The model utilizes advanced training techniques including gradient checkpointing via unsloth, flash attention, and employs the ChatML formatting standard. It was trained for 2 epochs using 8x H100 GPUs with careful optimization parameters including a learning rate of 5e-6 and cosine scheduler.
- Uses paged_adamw_8bit optimizer with gradient accumulation
- Implements flash attention and liger optimizations
- Supports sequence lengths up to 32768 tokens
- Employs sample packing for efficient training
Core Capabilities
- Advanced roleplay interactions with Claude-like prose quality
- Supports traditional RP scenarios with high coherence
- Handles complex prompting with ChatML format
- Optimal performance with temperature 1.1 and min_p 0.1
Frequently Asked Questions
Q: What makes this model unique?
The model combines the roleplay capabilities of Hamanasu-QwQ-V2-RP with Claude-style prose, creating a unique blend of creative and coherent interactions. The extensive training on specialized datasets and optimization for roleplay scenarios sets it apart from general-purpose LLMs.
Q: What are the recommended use cases?
The model excels in traditional roleplay scenarios, character interactions, and narrative generation. It's particularly suited for users seeking Claude-like prose quality in their roleplay interactions.
