What are the hardware requirements for Tiny Llm Tinystories 30M?

Tiny Llm Tinystories 30M requires approximately 0.1 GB of VRAM and supports a context window of 0.5K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tiny Llm Tinystories 30M and how large is it?

Tiny Llm Tinystories 30M is developed by CoolDip00, a model with 30m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Tiny Llm Tinystories 30M?

Tiny Llm Tinystories 30M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tiny Llm Tinystories 30M by CoolDip00 — VRAM 0.1GB, 0.5K context

Name: Tiny Llm Tinystories 30M
Author: CoolDip00

Tiny Llm Tinystories 30M is an open-source language model by CoolDip00. Features: 30m LLM, VRAM: 0.1GB, Context: 0.5K, License: mit, LLM Explorer Score: 0.33.

Arxiv:2305.07759 Dataset:roneneldan/tinystories En Endpoints compatible From-scratch Llama Region:us Safetensors Story-generation Tinystories

Model Card on HF 🤗: https://huggingface.co/CoolDip00/tiny-llm-tinystories-30m

Tiny Llm Tinystories 30M Parameters and Internals

LLM Name	Tiny Llm Tinystories 30M
Repository 🤗	https://huggingface.co/CoolDip00/tiny-llm-tinystories-30m
Model Size	30m
Required VRAM	0.1 GB
Updated	2026-11-09
Maintainer	CoolDip00
Model Type	llama
Model Files	0.1 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	mit
Context Length	512
Model Max Length	512
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Vocabulary Size	8192

Rank the Tiny Llm Tinystories 30M 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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