Llama2 22B Blocktriangular by chargoddard

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Llama2 22B Blocktriangular is an open-source language model by chargoddard. Features: 22b LLM, VRAM: 43.7GB, Context: 4K, LLM Explorer Score: 0.12, Arc: 58.5, HellaSwag: 82.6, MMLU: 54.6, GSM8K: 9.8.

Dataset:togethercomputer/redpa...   Endpoints compatible   Llama   Llama2   Pytorch   Region:us   Sharded

Llama2 22B Blocktriangular Benchmarks

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

Llama2 22B Blocktriangular Parameters and Internals

Model Type 
large language model
Use Cases 
Primary Use Cases:
Not intended for direct use, Meant as a base for further tuning and merging
Training Details 
Data Sources:
togethercomputer/RedPajama-Data-1T-Sample
Data Volume:
Twice the fine-tuning tokens compared to llama2-22b
Methodology:
BLOCK_DIAGONAL=false in the merge
LLM NameLlama2 22B Blocktriangular
Repository 🤗https://huggingface.co/chargoddard/llama2-22b-blocktriangular 
Model Size22b
Required VRAM43.7 GB
Updated2026-05-26
Maintainerchargoddard
Model Typellama
Model Files  9.8 GB: 1-of-5   10.0 GB: 2-of-5   9.9 GB: 3-of-5   9.9 GB: 4-of-5   4.1 GB: 5-of-5
Model ArchitectureLlamaForCausalLM
Context Length4098
Model Max Length4098
Transformers Version4.32.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than chargoddard/llama2-22b-blocktriangular.

Rank the Llama2 22B Blocktriangular 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