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LiteLlama 460M 1T by ahxt

 »  All LLMs  »  ahxt  »  LiteLlama 460M 1T   URL Share it on

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  Autotrain compatible   Dataset:redpajama   En   Endpoints compatible   Litellama   Llama   Llama2   Llama2 architecture   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/ahxt/LiteLlama-460M-1T 

LiteLlama 460M 1T Benchmarks

ARC: 24.83 vs 96.7 (so35)-74.3%
HellaSwag: 38.39 vs 95.3 (gpt4)-59.7%
MMLU: 25.96 vs 88.3 (so35)-70.6%
TruthfulQA: 41.59 vs 59 (gpt4)-29.5%
WinoGrande: 50.2 vs 87.5 (gpt4)-42.6%
LLME Score: 0.25706
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LiteLlama 460M 1T (ahxt/LiteLlama-460M-1T)

LiteLlama 460M 1T Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Commercial Applications
Applications:
Text Generation
Additional Notes 
The model is compact and experimental with significantly reduced parameter size compared to its base model LLaMa 2.
Training Details 
Data Sources:
RedPajama
Data Volume:
0.98 trillion tokens
Context Length:
1024
LLM NameLiteLlama 460M 1T
Repository 🤗https://huggingface.co/ahxt/LiteLlama-460M-1T 
Model Size460m
Required VRAM0.9 GB
Updated2025-02-05
Maintainerahxt
Model Typellama
Model Files  0.9 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length1024
Model Max Length1024
Transformers Version4.31.0
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size50304
Torch Data Typebfloat16
Errorsreplace

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Rank the LiteLlama 460M 1T 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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