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OpenELM 450M Instruct by apple

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  45291   
  Arxiv:2404.14619   Autotrain compatible   Custom code   Instruct   Openelm   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/apple/OpenELM-450M-Instruct 

OpenELM 450M Instruct Benchmarks

LLME Score: 0.26827
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OpenELM 450M Instruct (apple/OpenELM-450M-Instruct)

OpenELM 450M Instruct Parameters and Internals

Model Type 
Language Model
Use Cases 
Areas:
open research
Limitations:
No safety guarantees for outputs
Considerations:
Users should conduct thorough safety testing and implement appropriate filtering.
Additional Notes 
Supports pre-trained and instruction-tuned models with sizes varying from 270M to 3B parameters. Package includes data prep, training, fine-tuning, evaluation, checkpoints, and logs.
Training Details 
Data Sources:
RefinedWeb, deduplicated PILE, subset of RedPajama, subset of Dolma v1.6
Data Volume:
~1.8 trillion tokens
Methodology:
layer-wise scaling strategy within transformer layers
Input Output 
Input Format:
Plain text
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Use appropriate batch sizes and token speculation for faster generation.
LLM NameOpenELM 450M Instruct
Repository 🤗https://huggingface.co/apple/OpenELM-450M-Instruct 
Model Size450m
Required VRAM0.9 GB
Updated2025-01-20
Maintainerapple
Model Typeopenelm
Instruction-BasedYes
Model Files  0.9 GB
Model ArchitectureOpenELMForCausalLM
Licenseother
Transformers Version4.39.3
Vocabulary Size32000
Torch Data Typebfloat16

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Rank the OpenELM 450M Instruct 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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