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Mega Ar 126M 4K by BEE-spoke-data

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Mega Ar 126M 4K is an open-source language model by BEE-spoke-data. Features: 126m LLM, VRAM: 0.5GB, License: apache-2.0, LLM Explorer Score: 0.12.

  Arxiv:2209.10655 Dataset:bee-spoke-data/knowled... Dataset:bee-spoke-data/wikiped...   Dataset:jeankaddour/minipile   En   Endpoints compatible   Mega   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/BEE-spoke-data/mega-ar-126m-4k 

Mega Ar 126M 4K Benchmarks

LLME Score: 0.11905
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mega Ar 126M 4K (BEE-spoke-data/mega-ar-126m-4k)
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Mega Ar 126M 4K Parameters and Internals

Model Type 
text generation
Additional Notes 
This model is interesting because it's not technically a transformer despite being a language model.
Supported Languages 
en (High proficiency)
Training Details 
Data Sources:
JeanKaddour/minipile, BEE-spoke-data/wikipedia-20230901.en-deduped, BEE-spoke-data/knowledge-inoc-concat-v1
Methodology:
train-from-scratch
Context Length:
4096
Model Architecture:
mega
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Given the model's small size and architecture, it's best to leverage its longer context by adding input context to 'see more' rather than 'generate more'.
LLM NameMega Ar 126M 4K
Repository 🤗https://huggingface.co/BEE-spoke-data/mega-ar-126m-4k 
Model Size126m
Required VRAM0.5 GB
Updated2026-05-21
MaintainerBEE-spoke-data
Model Typemega
Model Files  0.5 GB
Supported Languagesen
Model ArchitectureMegaForCausalLM
Licenseapache-2.0
Transformers Version4.36.2
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50304
Torch Data Typefloat32

Rank the Mega Ar 126M 4K 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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