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SmolLM2 360M by HuggingFaceTB

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SmolLM2 360M is an open-source language model by HuggingFaceTB. Features: 360m LLM, VRAM: 0.7GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.26.

  Arxiv:2502.02737   Deploy:azure   En   Endpoints compatible   Llama   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/HuggingFaceTB/SmolLM2-360M 

SmolLM2 360M Benchmarks

MMLU Pro: 1.88
MUSR: 7.73
BBH: 5.54
IFEval: 21.15 vs 88 (so35)-76%
MATH Lvl 5: 1.21
LLME Score: 0.2619
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SmolLM2 360M (HuggingFaceTB/SmolLM2-360M)
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SmolLM2 360M Parameters and Internals

Model Type 
language model, instruction model
Use Cases 
Primary Use Cases:
text rewriting, summarization, function calling
Limitations:
Primarily understands and generates content in English, Generated content may not be factually accurate or logically consistent, Bias may be present in the training data
Considerations:
Use as assistive tools, always verify critical information
Supported Languages 
en (High proficiency)
Training Details 
Data Sources:
FineWeb-Edu, DCLM, The Stack
Data Volume:
4 trillion tokens
Methodology:
Supervised fine-tuning and Direct Preference Optimization (DPO)
Hardware Used:
64 H100 GPUs
Model Architecture:
Transformer decoder
Input Output 
Accepted Modalities:
text
LLM NameSmolLM2 360M
Repository 🤗https://huggingface.co/HuggingFaceTB/SmolLM2-360M 
Model Size360m
Required VRAM0.7 GB
Updated2026-04-10
MaintainerHuggingFaceTB
Model Typellama
Model Files  0.7 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.40.1
Tokenizer ClassGPT2Tokenizer
Vocabulary Size49152
Torch Data Typebfloat16

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TwinSmolLM2 360M8K / 0.7 GB50
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Smollm2 360M Sft SmallThoughts8K / 0.7 GB50
SolaraV2 Coder 05118K / 0.7 GB51
SmolLM2 360M Rickified8K / 1.4 GB90
BrainrotLM Assistant 362M8K / 0 GB70
Note: green Score (e.g. "73.2") means that the model is better than HuggingFaceTB/SmolLM2-360M.

Rank the SmolLM2 360M 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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