Sakura SOLAR Instruct DPO V2.8.0bpw H8 EXL2 by LoneStriker

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  Autotrain compatible   Conversational Dataset:argilla/distilabel-mat...   En   Endpoints compatible   Exl2   Instruct   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Sakura SOLAR Instruct DPO V2.8.0bpw H8 EXL2 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Sakura SOLAR Instruct DPO V2.8.0bpw H8 EXL2 (LoneStriker/Sakura-SOLAR-Instruct-DPO-v2-8.0bpw-h8-exl2)

Sakura SOLAR Instruct DPO V2.8.0bpw H8 EXL2 Parameters and Internals

Model Type 
text generation
Additional Notes 
Model uses 16-bit floating point precision.
Supported Languages 
en (Proficient)
Training Details 
Data Sources:
argilla/distilabel-math-preference-dpo
Methodology:
Using DPO method.
LLM NameSakura SOLAR Instruct DPO V2.8.0bpw H8 EXL2
Repository ๐Ÿค—https://huggingface.co/LoneStriker/Sakura-SOLAR-Instruct-DPO-v2-8.0bpw-h8-exl2 
Required VRAM10.9 GB
Updated2024-12-22
MaintainerLoneStriker
Model Typellama
Instruction-BasedYes
Model Files  8.6 GB: 1-of-2   2.3 GB: 2-of-2
Supported Languagesen
Quantization Typeexl2
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-sa-4.0
Context Length4096
Model Max Length4096
Transformers Version4.34.1
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Sakura-SOLAR-Instruct-DPO-v2-8.0bpw-h8-exl2.

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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 v20241217