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Tiny Lm by sbintuitions

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Tiny Lm is an open-source language model by sbintuitions. Features: LLM, VRAM: 0.1GB, Context: 2K, License: mit, LLM Explorer Score: 0.17.

  Dataset:wikipedia   En   Endpoints compatible   Ja   Llama   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/sbintuitions/tiny-lm 

Tiny Lm Benchmarks

LLME Score: 0.16725
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tiny Lm (sbintuitions/tiny-lm)
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Tiny Lm Parameters and Internals

Model Type 
language model
Additional Notes 
This repository provides a tiny 16M parameters language model for debugging and testing purposes.
Supported Languages 
en (English), ja (Japanese)
Training Details 
Data Sources:
English Wikipedia, Japanese Wikipedia
Data Volume:
25B tokens
Methodology:
traditional language modelling objective
Model Architecture:
4-layer, 512-hidden-size transformer-based language model
LLM NameTiny Lm
Repository 🤗https://huggingface.co/sbintuitions/tiny-lm 
Required VRAM0.1 GB
Updated2026-04-07
Maintainersbintuitions
Model Typellama
Model Files  0.1 GB
Supported Languagesja en
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Transformers Version4.32.0
Tokenizer ClassT5Tokenizer
Padding Token<pad>
Vocabulary Size51200
Torch Data Typefloat32

Best Alternatives to Tiny Lm

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Context / RAM
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LWM Text Chat 512K512K / 13.5 GB72
LWM Text 512K512K / 13.5 GB52
LWM Text 256K256K / 13.5 GB113
LWM Text Chat 256K256K / 13.5 GB63
Pallas 0.5 LASER 0.1195K / 68.9 GB18882
SnorTTS Indic V0128K / 9.5 GB81721
Orpheus AUS128K /  GB50
Llama 3.1 Medprm Reward V1.0128K / 16.1 GB11016
Finetuning Health Ci128K / 6.5 GB22
LLaMA Mesh128K / 16.1 GB452181
Note: green Score (e.g. "73.2") means that the model is better than sbintuitions/tiny-lm.

Rank the Tiny Lm 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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Release v20260328a
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