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Open-weight model

ocr-freeform-test

by Jungkookjeon1994 Jungkookjeon1994/ocr-freeform-test

ocr-freeform-test is an open-weight model from Jungkookjeon1994, released under Creative Commons Attribution 4.0. It has 16,576 parameters and a 128-token context. At 16-bit it needs about 0 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

This repository contains a working research note about OCR Freeform. It organizes motivation, related work, a falsifiable hypothesis, and an evaluation plan. It is not presented as a completed paper or a release of trained models.

Parameters16,576
Context128
Weights66.8 KB
Licensecc-by-4.0
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve ocr-freeform-test (16,576 parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 0.0 GB 0.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 0.0 GB 0.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 0.0 GB 0.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 18, 2026.

ocr-freeform-test on every accelerator the SAVRN Index prices, at every precision

Model Card

By Jungkookjeon1994, published under cc-by-4.0, revision c9590b50c828.

This repository contains a working research note about OCR Freeform. It organizes motivation, related work, a falsifiable hypothesis, and an evaluation plan. It is not presented as a completed paper or a release of trained models. - the scope of the research question and likely confounders - a proposed comparison with matched baselines - concrete evaluation context such as FUNSD, SROIE, and CORD - reproducibility checks, failure modes, and open questions - topic-relevant references Start with analysis.md for the full note. Sections labeled as plans or hypotheses should not be interpreted as experimental results. If results are added later, they should include dataset versions, commands…

Read Jungkookjeon1994's full model card

Notes on OCR Freeform

Repository summary

This repository contains a working research note about OCR Freeform. It organizes motivation, related work, a falsifiable hypothesis, and an evaluation plan. It is not presented as a completed paper or a release of trained models.

What is covered

  • the scope of the research question and likely confounders
  • a proposed comparison with matched baselines
  • concrete evaluation context such as FUNSD, SROIE, and CORD
  • reproducibility checks, failure modes, and open questions
  • topic-relevant references

How to read this repository

Start with analysis.md for the full note. Sections labeled as plans or hypotheses should not be interpreted as experimental results. If results are added later, they should include dataset versions, commands, seeds, hardware, and raw logs.

Scope and limitations

The note is intentionally exploratory. It does not claim benchmark improvements, completed ablations, released code, or a trained checkpoint. References and proposed datasets provide a starting point for verification rather than evidence that the study has already been run.

Files

  • analysis.md — primary artifact
  • README.md — this documentation

License

Released under cc-by-4.0. Review the source-data terms separately when this repository is used with external datasets.

Configuration

Architecture
CustomResearchModel
Context length (tokens)
128
Layers
6
Hidden size
128
Feed-forward size
256
Attention heads
4
Model type
transformer

Identity and Version

Repository
Jungkookjeon1994/ocr-freeform-test
Publisher
Jungkookjeon1994
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
16,576 parameters
Languages
ocr-freeform
Revision
c9590b50c828a18653276298e72b3cfbe1b2e85b
First published
2026-10-03
Last updated
2026-10-03

Files and Weights

6 files, 73.5 KB in total. The weights are 1 file totalling 66.8 KB in safetensors.

Weights1 file · 66.8 KB
Configuration2 files · 626 B
Documentation2 files · 4.6 KB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights66.8 KB 4ed61401de93
config.jsonConfiguration440 B —
training_args.jsonConfiguration186 B —
README.mdDocumentation1.5 KB —
analysis.mdDocumentation3.1 KB —
.gitattributesRepository1.5 KB —

License and Download

License
cc-by-4.0
Access
Open weights, no gate
Download size
66.8 KB
Download from Jungkookjeon1994

Released by Jungkookjeon1994 through its official repository on Hugging Face. Read the license.

Memory Requirements

PrecisionWeights in memory
As published66.8 KB
16-bit0.0 GB
8-bit0.0 GB
4-bit0.0 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About ocr-freeform-test

How much GPU memory does ocr-freeform-test need?

About 0 GB at 16-bit and 0 GB at 4-bit: the weights (16,576 parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run ocr-freeform-test on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use ocr-freeform-test commercially?

Yes. ocr-freeform-test is released under Creative Commons Attribution 4.0. CC BY 4.0 permits sharing and adapting the work, including commercially, provided the creator is credited and changes are indicated.

What is ocr-freeform-test's context length?

128 tokens, from the maximum position embeddings in its published configuration.