WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m
WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m is a 0.3 billion parameter language model, merged from several Gemma-3-270m-it fine-tunes, specifically designed for enhancing and expanding short prompts into detailed, context-rich descriptions. This model also incorporates capabilities for code generation and operates as an uncensored variant, making it suitable for research and experimental use where reduced safety filtering is acceptable. Its 32768 token context length supports processing longer inputs for prompt refinement and coding tasks.
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Model Overview
WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m is a 0.3 billion parameter language model, created by WithinUsAI through a SLERP merge of multiple fine-tuned Gemma-3-270m-it variants. This model is specifically engineered to enhance and expand concise prompts into more detailed and contextually rich descriptions. It also integrates capabilities for code generation, leveraging fine-tuning on datasets like microsoft/rStar-Coder.
Key Capabilities
- Prompt Enhancement: Excels at taking short prompts and expanding them into comprehensive, detailed descriptions.
- Code Generation: Incorporates fine-tuning for coding tasks, making it suitable for developers.
- Uncensored Output: Designed with significantly reduced safety filtering, allowing for a broader range of generated content.
Usage Warnings & Considerations
This model is an uncensored version, meaning its safety filtering has been substantially reduced. Users should be aware of the following:
- Sensitive Content Risk: It may generate sensitive, controversial, or inappropriate content.
- Not for All Audiences: Outputs may be unsuitable for public settings, underage users, or applications requiring strict content moderation.
- Legal & Ethical Responsibility: Users are solely responsible for ensuring their usage complies with local laws and ethical standards.
- Recommended Use: Best suited for research, testing, or controlled environments, rather than direct production or public-facing commercial applications.
- No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization, and the creators bear no responsibility for consequences arising from its use.