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Go Bruins V2 GGUF by TheBloke

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Dataset:athirdpath/dpo pairs-r...   Dataset:intel/orca dpo pairs   En   Gguf   Mistral   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/TheBloke/go-bruins-v2-GGUF 

Go Bruins V2 GGUF Benchmarks

LLME Score: 0.14048
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Go Bruins V2 GGUF Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
text generation, language understanding, sentiment analysis
Limitations:
Not recommended for illegal activities, harassment, professional advice or crisis situations
Additional Notes 
Further technical and implementation guidance available through Ryan Witzman on Discord: rwitz_.
Supported Languages 
en (high)
Training Details 
Data Sources:
Intel/orca_dpo_pairs, athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
Methodology:
Direct Preference Optimization (DPO) fine-tuning
Model Architecture:
mistral
Input Output 
Input Format:
Text
Accepted Modalities:
text
Output Format:
Generated text.
Release Notes 
Version:
2
Notes:
Go Bruins V2 is a fine-tuned version, offering improved performance over its predecessor.
LLM NameGo Bruins V2 GGUF
Repository 🤗https://huggingface.co/TheBloke/go-bruins-v2-GGUF 
Model NameGo Bruins v2
Model CreatorRyan Witzman
Base Model(s)  Go Bruins V2   rwitz/go-bruins-v2
Required VRAM3.1 GB
Updated2025-06-09
MaintainerTheBloke
Model Typemistral
Model Files  3.1 GB   3.8 GB   3.5 GB   3.2 GB   4.1 GB   4.4 GB   4.1 GB   5.0 GB   5.1 GB   5.0 GB   5.9 GB   7.7 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licensecc-by-nc-4.0
Go Bruins V2 GGUF (TheBloke/go-bruins-v2-GGUF)

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/go-bruins-v2-GGUF.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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