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ZephRP M7b by royallab

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  Autotrain compatible   En   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/royallab/ZephRP-m7b 

ZephRP M7b Benchmarks

LLME Score: 0.15151
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ZephRP M7b (royallab/ZephRP-m7b)
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ZephRP M7b Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
niche roleplaying forums
Limitations:
not intended for supplying factual information or advice
Additional Notes 
Bias similar to those observed in niche roleplaying forums. Not intended for factual information.
Training Details 
Data Sources:
LimaRP dataset
Methodology:
PEFT adapter training using LimaRP dataset
Hardware Used:
single L40 GPU
Input Output 
Input Format:
Alpaca instruction format
Accepted Modalities:
text
Performance Tips:
Length modifiers can be used to control response lengths.
LLM NameZephRP M7b
Repository 🤗https://huggingface.co/royallab/ZephRP-m7b 
Model Size7b
Required VRAM14.4 GB
Updated2025-09-16
Maintainerroyallab
Model Typemistral
Model Files  9.9 GB: 1-of-2   4.5 GB: 2-of-2
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

Quantized Models of the ZephRP M7b

Model
Likes
Downloads
VRAM
ZephRP M7b GGUF3393 GB
ZephRP M7b GPTQ254 GB
ZephRP M7b AWQ074 GB

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Note: green Score (e.g. "73.2") means that the model is better than royallab/ZephRP-m7b.

Rank the ZephRP M7b 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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Release v20241124
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