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Open Llama 0.7T 7B Open Instruct V1.1 by VMware

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  Autotrain compatible   Conversational Dataset:vmware/open-instruct-v...   En   Endpoints compatible   Instruct   Llama   Pytorch   Region:us   Safetensors   Sharded
Model Card on HF 🤗: https://huggingface.co/VMware/open-llama-0.7T-7B-open-instruct-v1.1 

Open Llama 0.7T 7B Open Instruct V1.1 Benchmarks

ARC: 46.67 vs 96.7 (so35)-51.7%
HellaSwag: 67.67 vs 95.3 (gpt4)-29%
MMLU: 28.55 vs 88.3 (so35)-67.7%
TruthfulQA: 37.6 vs 59 (gpt4)-36.3%
WinoGrande: 65.43 vs 87.5 (gpt4)-25.2%
GSM8K: 0.76 vs 96.4 (so35)-99.2%
LLME Score: 0.15954
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Open Llama 0.7T 7B Open Instruct V1.1 (VMware/open-llama-0.7T-7B-open-instruct-v1.1)

Open Llama 0.7T 7B Open Instruct V1.1 Parameters and Internals

Model Type 
transformer, conversational
Training Details 
Data Sources:
VMware/open-instruct-v1.1-oasst-dolly-hhrlhf
Data Volume:
700B tokens
Input Output 
Input Format:
Prompt template for instruction and response.
Accepted Modalities:
text
Output Format:
Text
Release Notes 
Version:
1.1
Notes:
Final version available with updates to Alpaca prompt template.
LLM NameOpen Llama 0.7T 7B Open Instruct V1.1
Repository 🤗https://huggingface.co/VMware/open-llama-0.7T-7B-open-instruct-v1.1 
Model Size7b
Required VRAM13.5 GB
Updated2025-03-14
MaintainerVMware
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensecc
Context Length2048
Model Max Length2048
Transformers Version4.28.1
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 VMware/open-llama-0.7T-7B-open-instruct-v1.1.

Rank the Open Llama 0.7T 7B Open Instruct V1.1 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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