xlsr-300m-dhonam is an open-weight model from Cynthia Jayne Amol. It has 315M parameters. At 16-bit it needs about 0.8 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 xlsr-300m-dhonam (315M 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 | 0.6 GB | 0.8 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.3 GB | 0.4 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.2 GB | 0.2 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.
xlsr-300m-dhonam on every accelerator the SAVRN Index prices, at every precision
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- Wav2Vec2ForCTC
- Layers
- 24
- Hidden size
- 1,024
- Feed-forward size
- 4,096
- Attention heads
- 16
- Vocabulary size
- 34
- Model type
- wav2vec2
Identity and Version
- Repository
- jayneamol/xlsr-300m-dhonam
- Publisher
- Cynthia Jayne Amol
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 315M parameters
- Languages
- Not stated by the source
- Revision
- 1d002dd28834b1046bc40160e03841de7dd139c4
- First published
- 2026-09-30
- Last updated
- 2026-10-01
Files and Weights
9 files, 1.3 GB in total. The weights are 2 files totalling 1.3 GB in bin, safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 1.3 GB | e551bae14f72 |
| training_args.bin | Weights | 5.3 KB | 3669ba36d290 |
| added_tokens.json | Configuration | 30 B | — |
| config.json | Configuration | 2.1 KB | — |
| preprocessor_config.json | Configuration | 214 B | — |
| processor_config.json | Configuration | 299 B | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer_config.json | Tokenizer | 1.2 KB | — |
| vocab.json | Tokenizer | 353 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 1.3 GB
Released by Cynthia Jayne Amol through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 1.3 GB |
| 16-bit | 0.6 GB |
| 8-bit | 0.3 GB |
| 4-bit | 0.2 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About xlsr-300m-dhonam
How much GPU memory does xlsr-300m-dhonam need?
About 0.8 GB at 16-bit and 0.2 GB at 4-bit: the weights (315M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run xlsr-300m-dhonam 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.