What are the hardware requirements for Learnia?

Learnia requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Learnia and how large is it?

Learnia is developed by Finisha-F-scratch, a model with 51.6m 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 Learnia?

Learnia is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Learnia by Finisha-F-scratch — VRAM 0.2GB

Name: Learnia
Author: Finisha-F-scratch

Learnia is an open-source language model by Finisha-F-scratch. Features: 51.6m LLM, VRAM: 0.2GB, License: other, LLM Explorer Score: 0.21.

En Endpoints compatible Gpt2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Finisha-F-scratch/Learnia

Learnia Parameters and Internals

LLM Name	Learnia
Repository 🤗	https://huggingface.co/Finisha-F-scratch/Learnia
Model Size	51.6m
Required VRAM	0.2 GB
Updated	2026-08-03
Maintainer	Finisha-F-scratch
Model Type	gpt2
Model Files	0.2 GB
Supported Languages	en
Model Architecture	GPT2LMHeadModel
License	other
Model Max Length	1024
Transformers Version	4.57.2
Tokenizer Class	GPT2Tokenizer
Padding Token	[PAD]
Vocabulary Size	50258
Activation Function	gelu_new

Rank the Learnia 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