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Go Bruins V2 GPTQ by TheBloke

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  4-bit   Autotrain compatible Dataset:athirdpath/dpo pairs-r...   Dataset:intel/orca dpo pairs   En   Gptq   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/go-bruins-v2-GPTQ 

Go Bruins V2 GPTQ Benchmarks

LLME Score: 0.12434
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Go Bruins V2 GPTQ (TheBloke/go-bruins-v2-GPTQ)
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Go Bruins V2 GPTQ Parameters and Internals

Model Type 
text generation, language understanding
Use Cases 
Areas:
research, content generation
Applications:
text generation, language understanding, sentiment analysis
Primary Use Cases:
Generating human-like text, Sentiment Analysis
Limitations:
Not suited for illegal activities, harassment, professional or crisis advice
Additional Notes 
The model is not recommended for situations where legal, professional advice, or crisis management is necessary.
Supported Languages 
English (fluent)
Training Details 
Data Sources:
athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
Methodology:
Direct Preference Optimization (DPO)
Model Architecture:
Fine-tuned on rwitz/go-bruins
Input Output 
Input Format:
Text prompt
Accepted Modalities:
text
Output Format:
Text response
Release Notes 
Version:
v2
Notes:
Finetuned on DPO method with improved NLP tasks performance.
LLM NameGo Bruins V2 GPTQ
Repository 🤗https://huggingface.co/TheBloke/go-bruins-v2-GPTQ 
Model NameGo Bruins v2
Model CreatorRyan Witzman
Base Model(s)  Go Bruins V2   rwitz/go-bruins-v2
Model Size1.2b
Required VRAM4.2 GB
Updated2025-09-23
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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