askalgore/Dolphin-Mistral-24B-Venice-Edition-heretic-2
The askalgore/Dolphin-Mistral-24B-Venice-Edition-heretic-2 is a 24 billion parameter Mistral-based language model, derived from dphn/Dolphin-Mistral-24B-Venice-Edition and further modified using Heretic v1.0.1. This model is specifically engineered for reduced refusal rates and enhanced steerability, allowing users to define alignment and system prompts without imposed ethical or safety guidelines. With a 32768 token context length, it is designed for general-purpose applications where user control over content generation and data privacy are paramount.
Loading preview...
Dolphin-Mistral-24B-Venice-Edition-heretic-2 Overview
This model is a 24 billion parameter Mistral-based language model, a "decensored" version of the original dphn/Dolphin-Mistral-24B-Venice-Edition, created using the Heretic v1.0.1 tool. It maintains a 32768 token context length.
Key Differentiators & Capabilities
- Reduced Refusals: Demonstrates a significantly lower refusal rate (6/100) compared to its base model (10/100), indicating a more permissive response generation.
- User-Controlled Alignment: Unlike many commercial models, Dolphin-Mistral-24B-Venice-Edition-heretic-2 emphasizes user control over alignment, system prompts, and data. It does not impose its own ethics or guidelines, allowing users to define the model's behavior.
- General Purpose: Aims to be a versatile, general-purpose model suitable for a wide range of applications, similar to models like ChatGPT or Claude, but with enhanced steerability.
- Stable System Prompting: Designed to prevent issues caused by external changes to system prompts or model versions, offering stability for businesses integrating AI into their products.
Performance & Usage
Performance metrics show a KL divergence of 0.01, indicating minimal deviation from the original model's statistical properties while achieving reduced refusals. The model maintains Mistral's default chat template and recommends using a relatively low temperature (e.g., temperature=0.15) for optimal output. It is compatible with various frameworks including ollama, LM Studio, Huggingface Transformers, vllm, sglang, and tgi.