WeniGPT Agents Llama3 5.0.79 SFT AWQ by Weni

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WeniGPT Agents Llama3 5.0.79 SFT AWQ is an open-source language model by Weni. Features: 70.6b LLM, VRAM: 39.9GB, Context: 8K, Quantized, Merged, LLM Explorer Score: 0.13.

  Merged Model   4-bit   Awq   Conversational   Endpoints compatible   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow

WeniGPT Agents Llama3 5.0.79 SFT AWQ Benchmarks

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 5.0.79 SFT AWQ Parameters and Internals

LLM NameWeniGPT Agents Llama3 5.0.79 SFT AWQ
Repository 🤗https://huggingface.co/Weni/WeniGPT-Agents-Llama3-5.0.79-SFT-AWQ 
Merged ModelYes
Model Size70.6b
Required VRAM39.9 GB
Updated2026-05-06
MaintainerWeni
Model Typellama
Model Files  5.0 GB: 1-of-9   4.9 GB: 2-of-9   4.9 GB: 3-of-9   4.9 GB: 4-of-9   4.9 GB: 5-of-9   4.9 GB: 6-of-9   4.9 GB: 7-of-9   3.4 GB: 8-of-9   2.1 GB: 9-of-9
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

Best Alternatives to WeniGPT Agents Llama3 5.0.79 SFT AWQ

Best Alternatives
Context / RAM
Downloads
Likes
Functionary Medium V3.0 AWQ8K / 39.9 GB50
Z MODEL2 V1 FUSED128K / 141.9 GB140
Z MODEL1 V1 FUSED128K / 141.9 GB140
Z MODEL4 V1 FUSED128K / 141.9 GB140
Z MODEL4 V1 FUSED128K / 141.9 GB140
Z MODEL2 V1 FUSED128K / 141.9 GB140
Z MODEL1 V1 FUSED128K / 141.9 GB140
Z MODEL5 V1 FUSED128K / 141.9 GB130
Z MODEL5 V1 FUSED128K / 141.9 GB130
Shi Ci V3 Robin128K / 141.9 GB97260
Note: green Score (e.g. "73.2") means that the model is better than Weni/WeniGPT-Agents-Llama3-5.0.79-SFT-AWQ.

Rank the WeniGPT Agents Llama3 5.0.79 SFT AWQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a