jeonsworld/CarbonVillain-en-10.7B-v5

TEXT GENERATIONConcurrency Cost:1Model Size:10.7BQuant:FP8Ctx Length:4kLicense:cc-by-nc-sa-4.0Architecture:Transformer Open Weights Cold

jeonsworld/CarbonVillain-en-10.7B-v5 is a 10.7 billion parameter experimental language model created by jeonsworld using Mergekit's slerp method. This model is specifically designed with an underlying objective to oppose indiscriminate carbon emissions, making it suitable for applications focused on environmental awareness or related ethical considerations. It processes inputs with a context length of 4096 tokens.

Loading preview...

Model Overview

The jeonsworld/CarbonVillain-en-10.7B-v5 is an experimental 10.7 billion parameter language model developed by jeonsworld. Its core design principle is to "oppose indiscriminate carbon emissions," suggesting a potential alignment for tasks related to environmental advocacy, sustainability discussions, or ethical AI applications concerning climate impact.

Technical Details

This model was created using Mergekit with the slerp (spherical linear interpolation) method, indicating it is a merge of multiple base models. It supports a context length of 4096 tokens.

Prompt Template

The model utilizes a specific prompt format:

### User:
{user}

### Assistant:
{asistant}

Evaluation

While the README mentions an evaluation section and a link to the Open LLM Leaderboard for CarbonVillain-en-10.7B-v4, specific benchmark scores for this v5 iteration are not provided directly within the README. Users interested in performance metrics should consult the linked leaderboard for the previous version or await updated evaluations for v5.

Use Cases

Given its stated purpose, this model could be particularly useful for:

  • Content Generation: Creating text related to environmental protection, climate change, or sustainable practices.
  • Ethical AI Research: Exploring how language models can be aligned with specific ethical or environmental objectives.
  • Thematic Applications: Developing applications where an underlying "anti-carbon emission" stance is desired in the model's responses.

Finetunes
1 models