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WeniGPT Agents Llama3 5.0.89 DPO AWQ by Weni

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WeniGPT Agents Llama3 5.0.89 DPO AWQ is an open-source language model by Weni. Features: 8b LLM, VRAM: 5.8GB, Context: 8K, Quantized, Merged, LLM Explorer Score: 0.13.

  Merged Model   4-bit   Awq   Conversational   Endpoints compatible   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Weni/WeniGPT-Agents-Llama3-5.0.89-DPO-AWQ 

WeniGPT Agents Llama3 5.0.89 DPO AWQ Benchmarks

LLME Score: 0.13465
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
WeniGPT Agents Llama3 5.0.89 DPO AWQ (Weni/WeniGPT-Agents-Llama3-5.0.89-DPO-AWQ)
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WeniGPT Agents Llama3 5.0.89 DPO AWQ Parameters and Internals

LLM NameWeniGPT Agents Llama3 5.0.89 DPO AWQ
Repository 🤗https://huggingface.co/Weni/WeniGPT-Agents-Llama3-5.0.89-DPO-AWQ 
Merged ModelYes
Model Size8b
Required VRAM5.8 GB
Updated2025-12-23
MaintainerWeni
Model Typellama
Model Files  4.7 GB: 1-of-2   1.1 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.41.0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Weni/WeniGPT-Agents-Llama3-5.0.89-DPO-AWQ.

Rank the WeniGPT Agents Llama3 5.0.89 DPO 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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