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Vicuna 33B V1.3 GGUF by sirovub

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Vicuna 33B V1.3 GGUF is an open-source language model by sirovub. Features: 33b LLM, VRAM: 34.6GB, Context: 2K, Quantized, HF Score: 58.5, LLM Explorer Score: 0.26, ELO: 1106, Arc: 62.1, HellaSwag: 83, MMLU: 59.2, TruthfulQA: 56.2, WinoGrande: 77, GSM8K: 13.7.

  Arxiv:2302.13971   Arxiv:2306.05685   Gguf   Llama   Pytorch   Q8   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/sirovub/vicuna-33b-v1.3-GGUF 

Vicuna 33B V1.3 GGUF Benchmarks

LMSys ELO: 1106 vs 1272 (so35)-13.1%
ARC: 62.12 vs 96.7 (so35)-35.8%
HellaSwag: 83 vs 95.3 (gpt4)-12.9%
MMLU: 59.22 vs 88.3 (so35)-32.9%
TruthfulQA: 56.16 vs 59 (gpt4)-4.8%
WinoGrande: 77.03 vs 87.5 (gpt4)-12%
GSM8K: 13.72 vs 96.4 (so35)-85.8%
LLME Score: 0.26297
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Vicuna 33B V1.3 GGUF (sirovub/vicuna-33b-v1.3-GGUF)
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Vicuna 33B V1.3 GGUF Parameters and Internals

Model Type 
auto-regressive language model
Use Cases 
Areas:
research on large language models and chatbots
Training Details 
Data Sources:
ShareGPT
Data Volume:
around 125K conversations
Methodology:
supervised instruction fine-tuning
Model Architecture:
transformer architecture
LLM NameVicuna 33B V1.3 GGUF
Repository 🤗https://huggingface.co/sirovub/vicuna-33b-v1.3-GGUF 
Base Model(s)  lmsys/vicuna-33b-v1.3   lmsys/vicuna-33b-v1.3
Model Size33b
Required VRAM34.6 GB
Updated2026-04-10
Maintainersirovub
Model Typellama
Model Files  34.6 GB
GGUF QuantizationYes
Quantization Typegguf|q8
Model ArchitectureLlamaForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.28.1
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Rank the Vicuna 33B V1.3 GGUF 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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