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Meta Llama 3 13B Instruct AWQ by solidrust

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Meta Llama 3 13B Instruct AWQ is an open-source language model by solidrust. Features: 13b LLM, VRAM: 8.8GB, Context: 8K, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

  4-bit   Autotrain compatible   Awq Base model:andrijdavid/meta-ll... Base model:quantized:andrijdav...   Conversational   Endpoints compatible   Instruct   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/solidrust/Meta-Llama-3-13B-Instruct-AWQ 

Meta Llama 3 13B Instruct AWQ Benchmarks

LLME Score: 0.13189
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3 13B Instruct AWQ (solidrust/Meta-Llama-3-13B-Instruct-AWQ)
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Meta Llama 3 13B Instruct AWQ Parameters and Internals

Model Type 
text-generation
LLM NameMeta Llama 3 13B Instruct AWQ
Repository 🤗https://huggingface.co/solidrust/Meta-Llama-3-13B-Instruct-AWQ 
Base Model(s)  Meta Llama 3 13B Instruct   andrijdavid/Meta-Llama-3-13B-Instruct
Model Size13b
Required VRAM8.8 GB
Updated2026-04-22
Maintainersolidrust
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   3.8 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.40.1
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

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Speechless Llama2 13B AWQ4K / 7.2 GB71
LoKuS 13B AWQ4K / 7.2 GB71

Rank the Meta Llama 3 13B Instruct AWQ 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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