Danbooru Llama by qwopqwop

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  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF ๐Ÿค—: https://huggingface.co/qwopqwop/danbooru-llama 

Danbooru Llama Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Danbooru Llama (qwopqwop/danbooru-llama)

Danbooru Llama Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Image descriptions, AI art generation
Applications:
Creative writing, Art-related AI projects
Primary Use Cases:
Text generation in art context
Additional Notes 
The model uses QLoRA, a low-rank adaptation technique for efficient training.
Training Details 
Data Sources:
Danbooru
Methodology:
Trained with QLoRA leveraging specific techniques for memory efficiency
Model Architecture:
Enhanced by merged QLoRA techniques
LLM NameDanbooru Llama
Repository ๐Ÿค—https://huggingface.co/qwopqwop/danbooru-llama 
Model Size7b
Required VRAM13.5 GB
Updated2025-05-18
Maintainerqwopqwop
Model Typellama
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2   10.0 GB: 1-of-2   3.5 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.30.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than qwopqwop/danbooru-llama.

Rank the Danbooru Llama Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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 v20241227