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Smol Llama 101M GQA by BEE-spoke-data

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Smol Llama 101M GQA is an open-source language model by BEE-spoke-data. Features: 101m LLM, VRAM: 0.4GB, Context: 1K, License: apache-2.0, LLM Explorer Score: 0.17, Arc: 23.5, HellaSwag: 28.7, MMLU: 24.4, GSM8K: 0.8.

Dataset:bee-spoke-data/wikiped...   Dataset:jeankaddour/minipile Dataset:mattymchen/refinedweb-... Dataset:pszemraj/simple wikipe...   Doi:10.57967/hf/1440   En   Endpoints compatible   Llama   Llama2   Region:us   Safetensors   Smol llama
Model Card on HF 🤗: https://huggingface.co/BEE-spoke-data/smol_llama-101M-GQA 

Smol Llama 101M GQA Benchmarks

ARC: 23.46 vs 96.7 (so35)-75.7%
HellaSwag: 28.73 vs 95.3 (gpt4)-69.9%
MMLU: 24.35 vs 88.3 (so35)-72.4%
GSM8K: 0.76 vs 96.4 (so35)-99.2%
LLME Score: 0.16657
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Smol Llama 101M GQA (BEE-spoke-data/smol_llama-101M-GQA)
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Smol Llama 101M GQA Parameters and Internals

Model Type 
text-generation
Use Cases 
Considerations:
Fine-tuning is recommended for specific tasks.
Additional Notes 
The checkpoint is the 'raw' pre-trained model and has not been tuned to a more specific task, indicating it should be fine-tuned before use in most cases.
Supported Languages 
en (English)
Training Details 
Data Sources:
JeanKaddour/minipile, pszemraj/simple_wikipedia_LM, BEE-spoke-data/wikipedia-20230901.en-deduped, mattymchen/refinedweb-3m
Methodology:
train-from-scratch
Context Length:
1024
Training Time:
5 compute-days
Hardware Used:
one GPU
Model Architecture:
768 hidden size, 6 layers, GQA (24 heads, 8 key-value)
Release Notes 
Version:
Revision 9c9c090
Date:
2023
Notes:
smol_llama-101M-GQA (First version), a small 101M param decoder model.
LLM NameSmol Llama 101M GQA
Repository 🤗https://huggingface.co/BEE-spoke-data/smol_llama-101M-GQA 
Model Size101m
Required VRAM0.4 GB
Updated2026-05-20
MaintainerBEE-spoke-data
Model Typellama
Model Files  0.4 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length1024
Model Max Length1024
Transformers Version4.34.1
Tokenizer ClassLlamaTokenizer
Vocabulary Size32128
Torch Data Typefloat32

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Rank the Smol Llama 101M GQA 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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