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Smol Llama 220M Open Instruct by BEE-spoke-data

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Smol Llama 220M Open Instruct is an open-source language model by BEE-spoke-data. Features: 220m LLM, VRAM: 0.4GB, Context: 2K, License: apache-2.0, Instruction-Based, HF Score: 29.2, LLM Explorer Score: 0.16, Arc: 25, HellaSwag: 29.7, MMLU: 26.1, TruthfulQA: 44.1, WinoGrande: 50.3.

Base model:bee-spoke-data/smol... Base model:finetune:bee-spoke-...   Dataset:vmware/open-instruct   Endpoints compatible   Instruct   Llama   Model-index   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/BEE-spoke-data/smol_llama-220M-open_instruct 

Smol Llama 220M Open Instruct Benchmarks

ARC: 25 vs 96.7 (so35)-74.1%
HellaSwag: 29.71 vs 95.3 (gpt4)-68.8%
MMLU: 26.11 vs 88.3 (so35)-70.4%
TruthfulQA: 44.06 vs 59 (gpt4)-25.3%
WinoGrande: 50.28 vs 87.5 (gpt4)-42.5%
LLME Score: 0.16009
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Smol Llama 220M Open Instruct (BEE-spoke-data/smol_llama-220M-open_instruct)
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Smol Llama 220M Open Instruct Parameters and Internals

Model Type 
text-generation
Additional Notes 
The model inference API parameters are set to sample with low temperature to ensure some variation in generations. Feel free to experiment with parameter settings.
Training Details 
Data Sources:
VMware/open-instruct
Input Output 
Input Format:
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
Output Format:
Responses to the instruction.
Performance Tips:
Experiment with inference parameters for improved performance.
LLM NameSmol Llama 220M Open Instruct
Repository 🤗https://huggingface.co/BEE-spoke-data/smol_llama-220M-open_instruct 
Base Model(s)  Smol Llama 220M GQA   BEE-spoke-data/smol_llama-220M-GQA
Model Size220m
Required VRAM0.4 GB
Updated2026-04-11
MaintainerBEE-spoke-data
Model Typellama
Instruction-BasedYes
Model Files  0.4 GB   0.0 GB
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32128
Torch Data Typebfloat16

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Rank the Smol Llama 220M Open 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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