73 lines
2.7 KiB
Markdown
73 lines
2.7 KiB
Markdown
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---
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license: apache-2.0
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language:
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- en
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base_model:
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- luvGPT/mistral-7b-uncensored
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tags:
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- Uncensored
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- text-generation
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- Quantized
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- Conversational
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---
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## Mistral-7B-Uncensored – Lightweight Instruction Model
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This repository provides the Mistral-7B-Uncensored model — a 7-billion-parameter conversational system designed for users who need responsive behavior with minimal automated filtering. Ideal for experimentation, offline usage, and custom alignment work.
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## Model Overview
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- **Model Name**: Mistral-7B-Uncensored
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- **Base Architecture**: Mistral 7B Transformer
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- **Developer / Maintainer**: luvGPT
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- **Training Type**: Instruction-oriented fine-tuning
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- **License**: Apache 2.0
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- **Intended Use**: High-control conversational model for private workflows
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## Model Purpose
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This variant focuses on delivering direct, adaptable responses rather than enforcing heavy policy constraints. It is intended for advanced users, researchers, and self-hosted environments who want to experiment with alignment behavior and prompt specialization.
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The design emphasizes flexibility, predictable structure during long dialogues, and support for workflows requiring thoughtful reasoning rather than rigid safety layers.
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Reference formatting inspiration from
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## Conversation Formatting
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The model operates effectively using a dialogue format similar to many Chat-style templates:
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```
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<|system|>
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System instructions here
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<|user|>
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User prompt
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<|assistant|>
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```
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## Capabilities
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- Tuned for instruction-following and productive dialogue
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- Reduced filtering to support research and customization
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- Handles contextual reasoning and multi-step tasks
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- Strong performance on creative writing, utility prompts, and open-ended discussion
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- Designed for local inference, CPU-friendly runtimes, and quantized deployment
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- Stable behavior over extended conversations
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## Suggested Applications
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- **Local assistant usage** : general chat, idea development
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- **Developer workflows** : code help, debugging, technical explanation
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- **Research environments** : prompt engineering, alignment studies
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- **Offline deployments** : privacy-sensitive or air-gapped environments
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- **Creative experimentation** : storytelling, prototyping characters
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## Notes & Considerations
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- The model is not a safety-filtered assistant; responsibility for usage rests with the operator.
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- Best suited for experienced users familiar with model governance and local deployment practices.
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## Acknowledgements
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Thanks to the Mistral developers and the open-model community for ecosystem support enabling accessible experimentation, as well as contributors who help evaluate and improve lightweight instruction models.
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