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Cognitive Hacker Gguf 0.2 by ebowwa

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  4bit Base model:quantized:unsloth/m... Base model:unsloth/mistral-7b-...   En   Endpoints compatible   Gguf   Mistral   Quantized   Region:us   Unsloth

Cognitive Hacker Gguf 0.2 Benchmarks

LLME Score: 0.21235
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Cognitive Hacker Gguf 0.2 Parameters and Internals

Model Type 
text-generation-inference, transformers
Additional Notes 
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
LLM NameCognitive Hacker Gguf 0.2
Repository 🤗https://huggingface.co/ebowwa/cognitive-hacker-gguf-0.2 
Base Model(s)  unsloth/mistral-7b-v0.3-bnb-4bit   unsloth/mistral-7b-v0.3-bnb-4bit
Model Size7b
Required VRAM4.4 GB
Updated2024-11-21
Maintainerebowwa
Model Typemistral
Model Files  4.4 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|4bit
Model ArchitectureAutoModel
Licenseapache-2.0
Cognitive Hacker Gguf 0.2 (ebowwa/cognitive-hacker-gguf-0.2)

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Note: green Score (e.g. "73.2") means that the model is better than ebowwa/cognitive-hacker-gguf-0.2.

Rank the Cognitive Hacker Gguf 0.2 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110
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