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Open-weight model

few-shot-multimodal-tutorial

by Lucas dubois02/few-shot-multimodal-tutorial

few-shot-multimodal-tutorial is an open-weight model from Lucas, released under Creative Commons Attribution 4.0. It has 49,600 parameters and a 512-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 is an exploratory note for Few Shot Multimodal. It records the intended comparison, likely confounders, and reproducibility requirements before any benchmark result is reported.

Parameters49,600
Context512
Weights198.9 KB
Licensecc-by-4.0
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve few-shot-multimodal-tutorial (49,600 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.

few-shot-multimodal-tutorial on every accelerator the SAVRN Index prices, at every precision

Model Card

By Lucas, published under cc-by-4.0, revision d6e46ea411b0.

This is an exploratory note for Few Shot Multimodal. It records the intended comparison, likely confounders, and reproducibility requirements before any benchmark result is reported. - the scope of the research question and likely confounders - a proposed comparison with matched baselines - concrete evaluation context such as task-appropriate public benchmarks named in the main note - reproducibility checks, failure modes, and open questions - topic-relevant references Start with reading.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…

Read Lucas's full model card

Notes on Few Shot Multimodal

Repository summary

This is an exploratory note for Few Shot Multimodal. It records the intended comparison, likely confounders, and reproducibility requirements before any benchmark result is reported.

What is covered

  • the scope of the research question and likely confounders
  • a proposed comparison with matched baselines
  • concrete evaluation context such as task-appropriate public benchmarks named in the main note
  • reproducibility checks, failure modes, and open questions
  • topic-relevant references

How to read this repository

Start with reading.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

  • reading.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)
512
Layers
3
Hidden size
384
Feed-forward size
768
Attention heads
8
Model type
transformer

Identity and Version

Repository
dubois02/few-shot-multimodal-tutorial
Publisher
Lucas
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
49,600 parameters
Languages
Not stated by the source
Revision
d6e46ea411b06f34d0b580d18015d0bd8f7e8a19
First published
2026-10-07
Last updated
2026-10-07

Files and Weights

6 files, 205.7 KB in total. The weights are 1 file totalling 198.9 KB in safetensors.

Weights1 file · 198.9 KB
Configuration2 files · 629 B
Documentation2 files · 4.7 KB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights198.9 KB 1dd709633444
config.jsonConfiguration440 B —
training_args.jsonConfiguration189 B —
README.mdDocumentation1.5 KB —
reading.mdDocumentation3.2 KB —
.gitattributesRepository1.5 KB —

License and Download

License
cc-by-4.0
Access
Open weights, no gate
Download size
198.9 KB
Download from Lucas

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

Memory Requirements

PrecisionWeights in memory
As published198.9 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 few-shot-multimodal-tutorial

How much GPU memory does few-shot-multimodal-tutorial need?

About 0 GB at 16-bit and 0 GB at 4-bit: the weights (49,600 parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run few-shot-multimodal-tutorial 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 few-shot-multimodal-tutorial commercially?

Yes. few-shot-multimodal-tutorial 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 few-shot-multimodal-tutorial's context length?

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