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OpenELM 270M Instruct by apple

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  1655   
  Arxiv:2404.14619   Autotrain compatible   Custom code   Instruct   Openelm   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/apple/OpenELM-270M-Instruct 

OpenELM 270M Instruct Benchmarks

LLME Score: 0.23507
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OpenELM 270M Instruct (apple/OpenELM-270M-Instruct)

OpenELM 270M Instruct Parameters and Internals

Model Type 
Transformer-based, Efficient Language Model
Use Cases 
Limitations:
Models may produce output that is inaccurate, biased, or objectionable.
Considerations:
Users must undertake thorough safety testing and implement filtering mechanisms.
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
Model Architecture:
Transformer
Responsible Ai Considerations 
Mitigation Strategies:
Electronic safeguards and user attributions are necessary.
Input Output 
Input Format:
Tokenized text inputs as prompts.
Accepted Modalities:
text
Output Format:
Generated text outputs.
Performance Tips:
Utilize speculative generation techniques for faster inference.
LLM NameOpenELM 270M Instruct
Repository 🤗https://huggingface.co/apple/OpenELM-270M-Instruct 
Model Size270m
Required VRAM0.5 GB
Updated2025-01-16
Maintainerapple
Model Typeopenelm
Instruction-BasedYes
Model Files  0.5 GB
Model ArchitectureOpenELMForCausalLM
Licenseother
Transformers Version4.39.3
Vocabulary Size32000
Torch Data Typebfloat16

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Rank the OpenELM 270M 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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Release v20241227
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