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OpenMath2 Llama3.1 8B by nvidia

 »  All LLMs  »  nvidia  »  OpenMath2 Llama3.1 8B   URL Share it on

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  Arxiv:2410.01560   Autotrain compatible Base model:finetune:meta-llama... Base model:meta-llama/llama-3....   Conversational Dataset:nvidia/openmathinstruc...   En   Endpoints compatible   Llama   Math   Nvidia   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/nvidia/OpenMath2-Llama3.1-8B 

OpenMath2 Llama3.1 8B Benchmarks

LLME Score: 0.29168
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OpenMath2 Llama3.1 8B (nvidia/OpenMath2-Llama3.1-8B)

OpenMath2 Llama3.1 8B Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
math domain
Primary Use Cases:
math problem solving
Limitations:
not instructed for general data
Additional Notes 
Pipeline and models are fully open-sourced.
Supported Languages 
en (native)
Training Details 
Data Sources:
OpenMathInstruct-2
Methodology:
Finetuning
Input Output 
Input Format:
System/User/Assistant tokens (chat format)
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Recommended to use instructions in provided repository for inference.
LLM NameOpenMath2 Llama3.1 8B
Repository 🤗https://huggingface.co/nvidia/OpenMath2-Llama3.1-8B 
Base Model(s)  meta-llama/Llama-3.1-8B   meta-llama/Llama-3.1-8B
Model Size8b
Required VRAM16.1 GB
Updated2024-12-06
Maintainernvidia
Model Typellama
Model Files  10.0 GB: 1-of-2   6.1 GB: 2-of-2
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensellama3.1
Context Length131072
Model Max Length131072
Transformers Version4.42.3
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

Quantized Models of the OpenMath2 Llama3.1 8B

Model
Likes
Downloads
VRAM
OpenMath 8B GGUF71984 GB

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Note: green Score (e.g. "73.2") means that the model is better than nvidia/OpenMath2-Llama3.1-8B.

Rank the OpenMath2 Llama3.1 8B Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
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