What are the hardware requirements for Tiny Random Mbart?

Tiny Random Mbart requires a context window of 0.1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tiny Random Mbart and how large is it?

Tiny Random Mbart is developed by akreal, a model with 25.3k 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 Random Mbart?

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

Tiny Random Mbart by akreal — 0.1K context

Name: Tiny Random Mbart
Author: akreal

Tiny Random Mbart is an open-source language model by akreal. Features: 25.3k LLM, Context: 0.1K, LLM Explorer Score: 0.01.

Endpoints compatible Mbart Pytorch Region:us Safetensors Tf

Model Card on HF 🤗: https://huggingface.co/akreal/tiny-random-mbart

Tiny Random Mbart Parameters and Internals

Additional Notes

Changes made: use old format for `pytorch_model.bin`

LLM Name	Tiny Random Mbart
Repository 🤗	https://huggingface.co/akreal/tiny-random-mbart
Model Size	25.3k
Required VRAM	0 GB
Updated	2026-08-06
Maintainer	akreal
Model Type	mbart
Model Files	0.0 GB 0.0 GB
Model Architecture	AutoModel
Context Length	100
Model Max Length	100
Transformers Version	4.10.0.dev0
Vocabulary Size	99
Activation Function	gelu

Rank the Tiny Random Mbart capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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