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Llama 2 7B Miniplatypus by mlabonne

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  Autotrain compatible   Dataset:mlabonne/mini-platypus   Endpoints compatible   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mlabonne/llama-2-7b-miniplatypus 

Llama 2 7B Miniplatypus Benchmarks

LLME Score: 0.12372
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 2 7B Miniplatypus (mlabonne/llama-2-7b-miniplatypus)
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Llama 2 7B Miniplatypus Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
educational purposes
Limitations:
Not designed for inference
Additional Notes 
Model is specifically designed for educational purposes and not for production-level inference.
Training Details 
Data Sources:
mlabonne/guanaco-llama2-1k, garage-bAInd/Open-Platypus
Methodology:
Fine-tuned using QLoRA (4-bit precision)
Hardware Used:
Google Colab notebook with a T4 GPU
Input Output 
Input Format:
Format includes an instruction prompt with markers \[INST\] and [/INST]
Accepted Modalities:
text
Output Format:
text
LLM NameLlama 2 7B Miniplatypus
Repository 🤗https://huggingface.co/mlabonne/llama-2-7b-miniplatypus 
Model Size7b
Required VRAM13.5 GB
Updated2025-08-20
Maintainermlabonne
Model Typellama
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   3.6 GB: 3-of-3   10.0 GB: 1-of-2   3.5 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than mlabonne/llama-2-7b-miniplatypus.

Rank the Llama 2 7B Miniplatypus 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 v20241124
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