Open-weight model
furniture_use_data_partial_finetuning
by Kim223 kim223/furniture_use_data_partial_finetuning
furniture_use_data_partial_finetuning is an open-weight model from Kim223. It has 42M parameters and a 1,024-token context. At 16-bit it needs about 0.1 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 furniture_use_data_partial_finetuning (42M 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 | 0.1 GB | 0.1 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.
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- DetrForObjectDetection
- Context length (tokens)
- 1,024
- Layers
- 6
- Model type
- detr
Identity and Version
- Repository
- kim223/furniture_use_data_partial_finetuning
- Publisher
- Kim223
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 42M parameters
- Languages
- Not stated by the source
- Revision
- 7fbd42f9bffb6283376ba0bf53dc736bb875d037
- First published
- 2026-10-09
- Last updated
- 2026-10-09
Files and Weights
5 files, 166.5 MB in total. The weights are 2 files totalling 166.5 MB in bin, safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 166.5 MB | 966c4a10b708 |
| training_args.bin | Weights | 5.8 KB | a59a67f97a7c |
| config.json | Configuration | 1.4 KB | — |
| preprocessor_config.json | Configuration | 455 B | — |
| .gitattributes | Repository | 1.5 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 166.5 MB
Released by Kim223 through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 166.5 MB |
| 16-bit | 0.1 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 furniture_use_data_partial_finetuning
How much GPU memory does furniture_use_data_partial_finetuning need?
About 0.1 GB at 16-bit and 0 GB at 4-bit: the weights (42M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run furniture_use_data_partial_finetuning 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.
What is furniture_use_data_partial_finetuning's context length?
1,024 tokens, from the maximum position embeddings in its published configuration.