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@@ -7,6 +7,13 @@ license: llama3.1
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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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@@ -22,27 +29,25 @@ This model can be used in various applications where natural language processing
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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-llama3.1-8b-v22.2-131k
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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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-
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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 dataset 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 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