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Open Llama 7B V2 Open Instruct by VMware

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  Autotrain compatible   Dataset:vmware/open-instruct   En   Endpoints compatible   Instruct   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/VMware/open-llama-7b-v2-open-instruct 

Open Llama 7B V2 Open Instruct Benchmarks

LLME Score: 0.11985
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Open Llama 7B V2 Open Instruct (VMware/open-llama-7b-v2-open-instruct)

Open Llama 7B V2 Open Instruct Parameters and Internals

Model Type 
text-generation
Additional Notes 
Fast tokenizer results in incorrect encoding
Supported Languages 
en (English)
Training Details 
Data Sources:
VMware/open-instruct, Mosaic/Dolly-HHRLHF, filtered OASST1, ESNLI, ECQA, Strategy, CREAK, gsmk8, aqua, qasc
Methodology:
The model was trained using the Alpaca prompt template
Input Output 
Input Format:
Prompt template: 'Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:'
Accepted Modalities:
text
Output Format:
Generated text output
Performance Tips:
Use 'use_fast=False' for correct tokenization
LLM NameOpen Llama 7B V2 Open Instruct
Repository 🤗https://huggingface.co/VMware/open-llama-7b-v2-open-instruct 
Model Size7b
Required VRAM13.5 GB
Updated2025-02-22
MaintainerVMware
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2   10.0 GB: 1-of-2   3.5 GB: 2-of-2
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensecc-by-sa-3.0
Context Length2048
Model Max Length2048
Transformers Version4.30.2
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-7b-v2-open-instruct.

Rank the Open Llama 7B V2 Open Instruct 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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Release v20241227
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