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Rose 20B by tavtav

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  Autotrain compatible   En   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/tavtav/Rose-20B 

Rose 20B Benchmarks

LLME Score: 0.14035
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Rose 20B (tavtav/Rose-20B)
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Rose 20B Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
Roleplay scenarios
Additional Notes 
This model is experiment driven and may be merged with other Frankenmerge models for further capabilities.
Supported Languages 
en (fluent)
Training Details 
Data Sources:
Thorns-13B, Noromaid-13-v0.1.1
Methodology:
Experimental merging of layers from different models (Frankenmerge)
Input Output 
Input Format:
Alpaca format
Accepted Modalities:
text
LLM NameRose 20B
Repository 🤗https://huggingface.co/tavtav/Rose-20B 
Model Size20b
Required VRAM39.9 GB
Updated2025-09-23
Maintainertavtav
Model Typellama
Instruction-BasedYes
Model Files  9.9 GB: 1-of-5   9.9 GB: 2-of-5   9.9 GB: 3-of-5   10.0 GB: 4-of-5   0.2 GB: 5-of-5
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.36.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token[PAD]
Vocabulary Size32000
Torch Data Typefloat16

Quantized Models of the Rose 20B

Model
Likes
Downloads
VRAM
Rose 20B GGUF2910098 GB
Rose 20B GPTQ359710 GB
Rose Kimiko 20B250 GB
Rose 20B AWQ1710 GB

Best Alternatives to Rose 20B

Best Alternatives
Context / RAM
Downloads
Likes
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
...I Llama2 Ko En Instruct 20B V12K / 40.4 GB50
Rose 20B GPTQ4K / 10.5 GB5973
Rose 20B AWQ4K / 10.9 GB71
Note: green Score (e.g. "73.2") means that the model is better than tavtav/Rose-20B.

Rank the Rose 20B 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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