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LaMini Cerebras 111M by MBZUAI

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LaMini Cerebras 111M is an open-source language model by MBZUAI. Features: 111m LLM, VRAM: 0.5GB, License: cc-by-nc-4.0, LLM Explorer Score: 0.07.

  Arxiv:2304.14402   En   Endpoints compatible   Gpt2   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/MBZUAI/LaMini-Cerebras-111M 

LaMini Cerebras 111M Benchmarks

LLME Score: 0.06928
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LaMini Cerebras 111M (MBZUAI/LaMini-Cerebras-111M)
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LaMini Cerebras 111M Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research
Applications:
human instruction response, NLP tasks
Primary Use Cases:
responding to instructions in text
Limitations:
not for commercial use
Considerations:
Use with wrapper text for best performance.
Additional Notes 
The model is one of the LaMini-LM series and is presented in a paper on distilling models from large-scale instructions.
Supported Languages 
English (fluent)
Training Details 
Data Sources:
LaMini-instruction dataset
Data Volume:
2.58M samples
Methodology:
fine-tuning
LLM NameLaMini Cerebras 111M
Repository 🤗https://huggingface.co/MBZUAI/LaMini-Cerebras-111M 
Model Size111m
Required VRAM0.5 GB
Updated2026-03-29
MaintainerMBZUAI
Model Typegpt2
Model Files  0.5 GB
Supported Languagesen
Model ArchitectureGPT2LMHeadModel
Licensecc-by-nc-4.0
Model Max Length512
Transformers Version4.27.4
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size50258
Torch Data Typefloat32
Activation Functiongelu
Errorsreplace

Best Alternatives to LaMini Cerebras 111M

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Context / RAM
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Kitten 110M0K / 0.4 GB350
Testmodel0K / 0.3 GB18801
111M0K / 0.3 GB18612
Cerebras GPT 111M Instruction0K / 0.4 GB283
Note: green Score (e.g. "73.2") means that the model is better than MBZUAI/LaMini-Cerebras-111M.

Rank the LaMini Cerebras 111M 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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