Rose Kimiko 20B AWQ by TheBloke

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  4-bit   Awq Base model:adapter:chat-error/... Base model:chat-error/rose-kim...   Fp16   Generated from trainer   Llama   Peft   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Rose Kimiko 20B AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Rose Kimiko 20B AWQ (TheBloke/Rose-Kimiko-20B-AWQ)
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Rose Kimiko 20B AWQ Parameters and Internals

Model Type 
llama
Use Cases 
Primary Use Cases:
fix spelling from Rose 20B
Additional Notes 
AWQ is a low-bit weight quantization method supporting faster and efficient inference.
Training Details 
Methodology:
fine-tuned on the Kimiko dataset using ShareGPT/Vicuna format
Context Length:
4096
Hardware Used:
Massed Compute
Input Output 
Input Format:
Prompt template: Alpaca
Accepted Modalities:
text
Output Format:
Generated text in response to the given prompt.
LLM NameRose Kimiko 20B AWQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/Rose-Kimiko-20B-AWQ 
Model NameRose Kimiko 20B
Model CreatornRuaif
Base Model(s)  nRuaif/Rose-Kimiko-20B   nRuaif/Rose-Kimiko-20B
Model Size20b
Required VRAM10.9 GB
Updated2025-08-22
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   0.9 GB: 2-of-2
AWQ QuantizationYes
Quantization Typefp16|awq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token[PAD]
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Rose-Kimiko-20B-AWQ.

Rank the Rose Kimiko 20B AWQ 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 v20241124