Open-weight model
tiny-transformer-classification-ablation
by fitri Wijaya Fitriwijay/tiny-transformer-classification-ablation
tiny-transformer-classification-ablation is an open-weight model from fitri Wijaya, released under BSD 3-Clause License. It has 49,600 parameters. 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.
Runs On
What it takes to serve tiny-transformer-classification-ablation (49,600 parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also 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 22, 2026.
Model Card
Identity and Version
- Repository
- Fitriwijay/tiny-transformer-classification-ablation
- Publisher
- fitri Wijaya
- 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
- 4837e457e5009c8430a2bf2e607c6ecc701deece
- First published
- 2026-10-21
- Last updated
- 2026-10-21
License and Download
- License
- bsd-3-clause
- Access
- Open weights, no gate
Released by fitri Wijaya through its official repository on Hugging Face. Read the license.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| 16-bit | 0.0 GB |
| 8-bit | 0.0 GB |
| 4-bit | 0.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About tiny-transformer-classification-ablation
How much GPU memory does tiny-transformer-classification-ablation 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 tiny-transformer-classification-ablation 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 tiny-transformer-classification-ablation commercially?
Yes. tiny-transformer-classification-ablation is released under BSD 3-Clause License. The BSD 3-Clause License is permissive. It permits commercial use and redistribution with the copyright notice, and forbids using the authors' names to endorse derived products without permission.