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Rose 20B GPTQ by TheBloke

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  4-bit   Autotrain compatible Base model:quantized:tavtav/ro...   Base model:tavtav/rose-20b   En   Gptq   Instruct   Llama   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/Rose-20B-GPTQ 

Rose 20B GPTQ Benchmarks

LLME Score: 0.1278
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Rose 20B GPTQ (TheBloke/Rose-20B-GPTQ)
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Rose 20B GPTQ Parameters and Internals

Model Type 
llama, text-generation
Use Cases 
Areas:
research, commercial applications
Applications:
roleplay models
Primary Use Cases:
finetuning experiments
Additional Notes 
The model is robust and good at roleplay scenarios. It's a frankenmerge model known for its potential in finetuning experiments.
Input Output 
Input Format:
Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {prompt} ### Response:
LLM NameRose 20B GPTQ
Repository 🤗https://huggingface.co/TheBloke/Rose-20B-GPTQ 
Model NameRose 20B
Model CreatorTav
Base Model(s)  Rose 20B   tavtav/Rose-20B
Model Size20b
Required VRAM10.5 GB
Updated2025-09-23
MaintainerTheBloke
Model Typellama
Instruction-BasedYes
Model Files  10.5 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token[PAD]
Vocabulary Size32000
Torch Data Typefloat16

Best Alternatives to Rose 20B GPTQ

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Context / RAM
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Bagel 20B V04 Llama32K / 39.6 GB127
Bagel DPO 20B V04 Llama32K / 39.6 GB73
...lm2 1.7B Distilled GPT Oss 20B8K / 0 GB252
...runed Base PostPruneRetraining8K / 0 GB50
...lerLM 20M Instruct Pruned Sft58K / 0.1 GB60
Rose 20B4K / 39.9 GB186942
Rose 20B AWQ4K / 10.9 GB71
...I Llama2 Ko En Instruct 20B V12K / 40.4 GB50
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Rose-20B-GPTQ.

Rank the Rose 20B GPTQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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
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