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README.md
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language:
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- en
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pipeline_tag: text-generation
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---
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# Llama3.1-Dark-Enigma
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## Data Overview
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The model is built by merging several Llama 3.1 8B text models selected for their diverse layer weights. This fusion aims to leverage the strengths of each component, resulting in a more robust and versatile AI tool.
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- LongWriter-llama3.1-8b
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- Llama-3.1-Storm-8B
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- DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored
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- Llama3.1-8B-Enigma
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Those models were merged onto Llama3.1-vodka using mergekit's `model\_stock` method with equal weights.
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## Performance Evaluation
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While specific performance metrics are not provided, users can expect high-quality output when using effective prompting techniques and grounded input texts. The model's uncensored nature ensures it doesn't shy away from complex or sensitive topics.
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In fact, most of this
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## Limitations
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Users should note the following:
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- Do not rely solely on the model's output
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- As a 8B parameter model, it does poorly on closed book factual questions and answers.
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- For optimal performance, use good prompting strategies to guide the model effectively.
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- Be cautious when processing text that may contain biases or inaccuracies.
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- The quality may vary for languages other than English.
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- The model can't connect to the Internet and it doesn't know how to use specific APIs, libraries, or frameworks.
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## Bias and Fairness Analysis
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language:
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- en
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pipeline_tag: text-generation
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base_model:
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- OpenBuddy/openbuddy-llama3.1-8b-v22.2-131k
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- THUDM/LongWriter-llama3.1-8b
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- akjindal53244/Llama-3.1-Storm-8B
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- aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored
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- ValiantLabs/Llama3.1-8B-Enigma
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- agentlans/Llama3.1-vodka
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---
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# Llama3.1-Dark-Enigma
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## Data Overview
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The model is built by merging several Llama 3.1 8B text models selected for their diverse layer weights. This fusion aims to leverage the strengths of each component, resulting in a more robust and versatile AI tool.
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- [OpenBuddy/openbuddy-llama3.1-8b-v22.2-131k](https://huggingface.co/OpenBuddy/openbuddy-llama3.1-8b-v22.2-131k)
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- [THUDM/LongWriter-llama3.1-8b](https://huggingface.co/THUDM/LongWriter-llama3.1-8b)
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- [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B)
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- [aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored](https://huggingface.co/aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored)
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- [ValiantLabs/Llama3.1-8B-Enigma](https://huggingface.co/ValiantLabs/Llama3.1-8B-Enigma)
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Those models were merged onto [agentlans/Llama3.1-vodka](https://huggingface.co/agentlans/Llama3.1-vodka) using [mergekit](https://github.com/arcee-ai/mergekit)'s `model_stock` method where each model is equally weighted.
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## Performance Evaluation
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While specific performance metrics are not provided, users can expect high-quality output when using effective prompting techniques and grounded input texts. The model's uncensored nature ensures it doesn't shy away from complex or sensitive topics.
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In fact, most of this model card was generated by the model itself.
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## Limitations
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Users should note the following:
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- Do not rely solely on the model's output. Always validate its results.
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- As a 8B parameter model, it does poorly on closed book factual questions and answers.
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- For optimal performance, use good prompting strategies to guide the model effectively.
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- Be cautious when processing text that may contain biases or inaccuracies.
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- The model can't connect to the Internet and it doesn't know how to use specific APIs, libraries, or frameworks.
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## Bias and Fairness Analysis
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