Llama 3 LewdPlay 8B Evo AWQ by solidrust

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  4-bit   Autotrain compatible   Awq Base model:quantized:undi95/ll... Base model:undi95/llama-3-lewd...   Conversational   Endpoints compatible   Llama   Merge   Mergekit   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Llama 3 LewdPlay 8B Evo AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 LewdPlay 8B Evo AWQ (solidrust/Llama-3-LewdPlay-8B-evo-AWQ)

Llama 3 LewdPlay 8B Evo AWQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
AWQ is used for efficient, accurate, and fast low-bit weight quantization.
Input Output 
Input Format:
<|begin_of_text|><|start_header_id|>system<|end_header_id|> {system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|> {input}<|eot_id|><|start_header_id|>assistant<|end_header_id> {output}<|eot_id|>
Accepted Modalities:
text
Performance Tips:
Supports 4-bit quantization for faster inference.
LLM NameLlama 3 LewdPlay 8B Evo AWQ
Repository ๐Ÿค—https://huggingface.co/solidrust/Llama-3-LewdPlay-8B-evo-AWQ 
Base Model(s)  Llama 3 LewdPlay 8B Evo   Undi95/Llama-3-LewdPlay-8B-evo
Model Size8b
Required VRAM5.8 GB
Updated2024-12-22
Maintainersolidrust
Model Typellama
Model Files  4.7 GB: 1-of-2   1.1 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length8192
Model Max Length8192
Transformers Version4.38.2
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than solidrust/Llama-3-LewdPlay-8B-evo-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  
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