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S1 0.5B by 2stacks

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S1 0.5B is an open-source language model by 2stacks. Features: 0.5b LLM, VRAM: 2.5GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.17.

  Arxiv:2501.19393   Ar Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-0.5b-i...   Conversational   Dataset:simplescaling/s1k   De   En   Endpoints compatible   Es   Fr   Instruct   It   Ja   Ko   Pt   Qwen2   Region:us   Ru   Safetensors   Th   Vi   Zh
Model Card on HF 🤗: https://huggingface.co/2stacks/s1-0.5B 

S1 0.5B Benchmarks

LLME Score: 0.17494
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
S1 0.5B (2stacks/s1-0.5B)
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S1 0.5B Parameters and Internals

LLM NameS1 0.5B
Repository 🤗https://huggingface.co/2stacks/s1-0.5B 
Base Model(s)  Qwen/Qwen2.5-0.5B-Instruct   Qwen/Qwen2.5-0.5B-Instruct
Model Size0.5b
Required VRAM2.5 GB
Updated2026-05-18
Maintainer2stacks
Model Typeqwen2
Instruction-BasedYes
Model Files  2.5 GB   0.0 GB
Supported Languagesar de en es fr it ja ko pt ru th vi zh
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.46.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|fim_pad|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

Best Alternatives to S1 0.5B

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2 0.5B Abyme Merge3128K / 1.3 GB331
Qwen2 0.5B Abyme Merge2128K / 0.3 GB220
Qwen2.5 0.5B Instruct64K / 1 GB70
Qwen2.5 0.5B Instruct32K / 1 GB6089483505
Q SS 0.5B Reasoning Math32K / 1 GB592
...5 0.5B Instruct Abliterated Ru32K / 2 GB3790
BoyBarley Sparky V332K / 1 GB4230
Qwen2 0.5B Instruct32K / 1 GB1440477200
...ext Aware Abstention Qwen 0.5B32K / 2 GB480
DAC5.4 0.5B32K / 1 GB140
Note: green Score (e.g. "73.2") means that the model is better than 2stacks/s1-0.5B.

Rank the S1 0.5B 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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