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TW3 JRGL V2 by paloalma

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TW3 JRGL V2 is an open-source language model by paloalma. Features: 72b LLM, VRAM: 79.7GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.26.

  Merged Model   Davidkim205/rhea-72b-v0.5   Endpoints compatible   Llama   Mtsair/multiverse 70b   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/paloalma/TW3-JRGL-v2 

TW3 JRGL V2 Benchmarks

MMLU Pro: 42.87
GPQA: 14.54
MUSR: 20.7
BBH: 45.61
IFEval: 53.16 vs 88 (so35)-39.6%
MATH Lvl 5: 17.9
LLME Score: 0.26289
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TW3 JRGL V2 (paloalma/TW3-JRGL-v2)
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TW3 JRGL V2 Parameters and Internals

Additional Notes 
This model was developed under the supervision of Andre-Louis Rochet and Paul Lemaistre. It was sponsored by ECE engineering school and RunPod.
LLM NameTW3 JRGL V2
Repository 🤗https://huggingface.co/paloalma/TW3-JRGL-v2 
Merged ModelYes
Model Size72b
Required VRAM79.7 GB
Updated2026-04-25
Maintainerpaloalma
Model Typellama
Model Files  1.9 GB: 1-of-82   0.4 GB: 2-of-82   2.5 GB: 3-of-82   1.9 GB: 4-of-82   1.9 GB: 5-of-82   1.6 GB: 6-of-82   1.7 GB: 7-of-82   1.7 GB: 8-of-82   1.9 GB: 9-of-82   1.9 GB: 10-of-82   1.9 GB: 11-of-82   1.6 GB: 12-of-82   1.7 GB: 13-of-82   1.9 GB: 14-of-82   1.9 GB: 15-of-82   1.9 GB: 16-of-82   1.6 GB: 17-of-82   1.7 GB: 18-of-82   1.7 GB: 19-of-82   1.6 GB: 20-of-82   1.7 GB: 21-of-82   1.7 GB: 22-of-82   1.9 GB: 23-of-82   1.9 GB: 24-of-82   1.7 GB: 25-of-82   1.7 GB: 26-of-82   1.7 GB: 27-of-82   1.9 GB: 28-of-82   1.7 GB: 29-of-82   1.7 GB: 30-of-82   1.9 GB: 31-of-82   1.7 GB: 32-of-82   1.7 GB: 33-of-82   1.9 GB: 34-of-82   1.9 GB: 35-of-82   1.6 GB: 36-of-82   1.7 GB: 37-of-82   1.7 GB: 38-of-82   1.9 GB: 39-of-82   1.9 GB: 40-of-82   1.9 GB: 41-of-82   1.9 GB: 42-of-82   1.7 GB: 43-of-82   1.9 GB: 44-of-82   1.9 GB: 45-of-82
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.39.2
Vocabulary Size152064
Torch Data Typebfloat16

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Rank the TW3 JRGL V2 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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