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Open-weight model

grounded-language-base57

by Anna Szymanski annaszymanski/grounded-language-base57

grounded-language-base57 is an open-weight model from Anna Szymanski, released under MIT License. It has 33,088 parameters and a 256-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.

Reading notes and an experiment sketch for Grounded Language. The repository emphasizes what still needs to be tested instead of manufacturing scores or release claims.

Parameters33,088
Context256
Weights132.8 KB
Licensemit
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve grounded-language-base57 (33,088 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 19, 2026.

grounded-language-base57 on every accelerator the SAVRN Index prices, at every precision

Model Card

By Anna Szymanski, published under mit, revision 4cf5f11a314f.

Reading notes and an experiment sketch for Grounded Language. The repository emphasizes what still needs to be tested instead of manufacturing scores or release claims. - the scope of the research question and likely confounders - a proposed comparison with matched baselines - concrete evaluation context such as RefCOCO, Flickr30k, and Visual Genome - reproducibility checks, failure modes, and open questions - topic-relevant references Start with review.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. The note is…

Read Anna Szymanski's full model card

Notes on Grounded Language

Repository summary

Reading notes and an experiment sketch for Grounded Language. The repository emphasizes what still needs to be tested instead of manufacturing scores or release claims.

What is covered

  • the scope of the research question and likely confounders
  • a proposed comparison with matched baselines
  • concrete evaluation context such as RefCOCO, Flickr30k, and Visual Genome
  • reproducibility checks, failure modes, and open questions
  • topic-relevant references

How to read this repository

Start with review.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

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

License

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

Configuration

Architecture
CustomResearchModel
Context length (tokens)
256
Layers
6
Hidden size
256
Feed-forward size
1,024
Attention heads
2
Model type
transformer

Identity and Version

Repository
annaszymanski/grounded-language-base57
Publisher
Anna Szymanski
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
33,088 parameters
Languages
Not stated by the source
Revision
4cf5f11a314f9259ebb7f43ce1dd1ec4a66a79f8
First published
2026-10-06
Last updated
2026-10-06

Files and Weights

6 files, 139.5 KB in total. The weights are 1 file totalling 132.8 KB in safetensors.

Weights1 file · 132.8 KB
Configuration2 files · 628 B
Documentation2 files · 4.5 KB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights132.8 KB e3990cda2590
config.jsonConfiguration441 B —
training_args.jsonConfiguration187 B —
README.mdDocumentation1.4 KB —
review.mdDocumentation3.1 KB —
.gitattributesRepository1.5 KB —

License and Download

License
mit
Access
Open weights, no gate
Download size
132.8 KB
Download from Anna Szymanski

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

Memory Requirements

PrecisionWeights in memory
As published132.8 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 grounded-language-base57

How much GPU memory does grounded-language-base57 need?

About 0 GB at 16-bit and 0 GB at 4-bit: the weights (33,088 parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run grounded-language-base57 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 grounded-language-base57 commercially?

Yes. grounded-language-base57 is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.

What is grounded-language-base57's context length?

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