LUNA SOLARkrautLM Instruct AWQ by TheBloke

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  4-bit   Augmentation   Autotrain compatible   Awq Base model:fblgit/luna-solarkr... Base model:quantized:fblgit/lu...   Conversational Dataset:argilla/distilabel-mat...   De   Dpo   En   Finetuned   German   Instruct   Llama   Quantized   Region:us   Safetensors

LUNA SOLARkrautLM Instruct AWQ Benchmarks

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

LUNA SOLARkrautLM Instruct AWQ Parameters and Internals

LLM NameLUNA SOLARkrautLM Instruct AWQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/LUNA-SOLARkrautLM-Instruct-AWQ 
Model NameLuna SOLARkrautLM Instruct
Model CreatorFBL
Base Model(s)  LUNA SOLARkrautLM Instruct   fblgit/LUNA-SOLARkrautLM-Instruct
Model Size1.7b
Required VRAM6 GB
Updated2024-11-07
MaintainerTheBloke
Model Typesolar
Instruction-BasedYes
Model Files  6.0 GB
Supported Languagesen de
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length4096
Model Max Length4096
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16
LUNA SOLARkrautLM Instruct AWQ (TheBloke/LUNA-SOLARkrautLM-Instruct-AWQ)

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/LUNA-SOLARkrautLM-Instruct-AWQ.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803