ECE TW3 JRGL V5 by paloalma

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ECE TW3 JRGL V5 is an open-source language model by paloalma. Features: 72b LLM, VRAM: 159.6GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.25.

  Merged Model   Endpoints compatible   Ibivibiv/alpaca-dragon-72b-v1   Llama   Lora   Moreh/momo-72b-lora-1.8.7-dpo   Region:us   Safetensors   Sharded   Tensorflow

ECE TW3 JRGL V5 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

ECE TW3 JRGL V5 Parameters and Internals

Additional Notes 
This model is a "merge" type, specifically created using the MergeKit tool by combining two specified models: moreh/MoMo-72B-lora-1.8.7-DPO and ibivibiv/alpaca-dragon-72b-v1.
LLM NameECE TW3 JRGL V5
Repository 🤗https://huggingface.co/paloalma/ECE-TW3-JRGL-V5 
Merged ModelYes
Model Size72b
Required VRAM159.6 GB
Updated2026-04-13
Maintainerpaloalma
Model Typellama
Model Files  5.0 GB: 1-of-82   3.8 GB: 2-of-82   3.5 GB: 3-of-82   3.8 GB: 4-of-82   3.5 GB: 5-of-82   3.5 GB: 6-of-82   3.5 GB: 7-of-82   3.8 GB: 8-of-82   3.2 GB: 9-of-82   3.5 GB: 10-of-82   3.5 GB: 11-of-82   3.8 GB: 12-of-82   3.2 GB: 13-of-82   3.5 GB: 14-of-82   3.5 GB: 15-of-82   3.8 GB: 16-of-82   3.2 GB: 17-of-82   3.5 GB: 18-of-82   3.5 GB: 19-of-82   3.8 GB: 20-of-82   3.2 GB: 21-of-82   3.5 GB: 22-of-82   3.5 GB: 23-of-82   3.8 GB: 24-of-82   3.2 GB: 25-of-82   3.5 GB: 26-of-82   3.5 GB: 27-of-82   3.8 GB: 28-of-82   3.2 GB: 29-of-82   3.5 GB: 30-of-82   3.5 GB: 31-of-82   3.8 GB: 32-of-82   3.2 GB: 33-of-82   3.5 GB: 34-of-82   3.5 GB: 35-of-82   3.8 GB: 36-of-82   3.2 GB: 37-of-82   3.5 GB: 38-of-82   3.5 GB: 39-of-82   3.8 GB: 40-of-82   3.2 GB: 41-of-82   3.5 GB: 42-of-82   3.5 GB: 43-of-82   3.8 GB: 44-of-82   3.2 GB: 45-of-82
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.39.3
Vocabulary Size152064
LoRA ModelYes
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than paloalma/ECE-TW3-JRGL-V5.

Rank the ECE TW3 JRGL V5 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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Release v20260328a