Runs On
What it takes to serve master-vocal-trainer (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 Sep 18, 2026.
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
- 51
- Model type
- wav2vec2
Identity and Version
- Repository
- evteducation/master-vocal-trainer
- Publisher
- Ronald Lee
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 315M parameters
- Languages
- Not stated by the source
- Revision
- 009412516e603509ff80d5059ad47b2561f14e90
- First published
- 2026-05-26
- Last updated
- 2026-09-18
Files and Weights
15 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 | c4b9bb98a556 |
| training_args.bin | Weights | 5.2 KB | 976fdcc2e593 |
| added_tokens.json | Configuration | 30 B | — |
| config.json | Configuration | 2.1 KB | — |
| inspect_dataset.py | Configuration | 814 B | — |
| preprocessor_config.json | Configuration | 256 B | — |
| processor_config.json | Configuration | 299 B | — |
| special_tokens_map.json | Configuration | 520 B | — |
| LICENSE | Documentation | — | |
| README.md | Documentation | 71 B | — |
| voice_quality_test_model_v3.joblib | Other | 4.1 MB | 944b94c0f8ae |
| voice_quality_test_model_v5.joblib | Other | 4.6 MB | 442a73b16f4f |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer_config.json | Tokenizer | 6.7 KB | — |
| vocab.json | Tokenizer | 616 B | — |
License and Download
- License
- other
- Access
- Open weights, no gate
- Download size
- 1.3 GB
Released by Ronald Lee 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 master-vocal-trainer
How much GPU memory does master-vocal-trainer 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 master-vocal-trainer 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 license is master-vocal-trainer released under?
other, as its publisher declares it. Read the license text before commercial use.