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Open Llama 0.3T 7B Instruct Dolly Hhrlhf by VMware

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Open Llama 0.3T 7B Instruct Dolly Hhrlhf is an open-source language model by VMware. Features: 7b LLM, VRAM: 13.5GB, Context: 2K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.07.

  Dataset:mosaicml/dolly hhrlhf   En   Endpoints compatible   Instruct   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/VMware/open-llama-0.3T-7B-instruct-dolly-hhrlhf 

Open Llama 0.3T 7B Instruct Dolly Hhrlhf Benchmarks

LLME Score: 0.07167
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Open Llama 0.3T 7B Instruct Dolly Hhrlhf (VMware/open-llama-0.3T-7B-instruct-dolly-hhrlhf)
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Open Llama 0.3T 7B Instruct Dolly Hhrlhf Parameters and Internals

Model Type 
text generation
Additional Notes 
The model uses a BOS token for tokenizer initialization based on its training setup.
Supported Languages 
en (proficient)
Input Output 
Input Format:
Prompt with an instruction.
Accepted Modalities:
text
Output Format:
Text
LLM NameOpen Llama 0.3T 7B Instruct Dolly Hhrlhf
Repository 🤗https://huggingface.co/VMware/open-llama-0.3T-7B-instruct-dolly-hhrlhf 
Model Size7b
Required VRAM13.5 GB
Updated2026-04-21
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
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.28.1
Tokenizer ClassLlamaTokenizer
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-0.3T-7B-instruct-dolly-hhrlhf.

Rank the Open Llama 0.3T 7B Instruct Dolly Hhrlhf 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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