Wav2Vec_VinData_Full is an open-weight model from Ngo Hoang Huy. It has 316M 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 Wav2Vec_VinData_Full (316M 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.
Wav2Vec_VinData_Full 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
- 94
- Model type
- wav2vec2
Identity and Version
- Repository
- hoanghuy2000gl/Wav2Vec_VinData_Full
- Publisher
- Ngo Hoang Huy
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 316M parameters
- Languages
- Not stated by the source
- Revision
- cb4f84cce5f9c67115ae23c45d30a19b653f7f27
- First published
- 2026-09-19
- Last updated
- 2026-09-20
Files and Weights
23 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 | 1417c4e7ed15 |
| training_args.bin | Weights | 5.3 KB | eaaf4cf275d0 |
| config.json | Configuration | 2.3 KB | — |
| preprocessor_config.json | Configuration | 214 B | — |
| runs/Sep19_11-49-18_cb752353c8e5/events.out.tfevents.1789818558.cb752353c8e5.21369.0 | Other | 6.0 KB | 204e7db1baeb |
| runs/Sep19_12-26-25_0ee812ae912a/events.out.tfevents.1789820785.0ee812ae912a.2917.0 | Other | 7.3 KB | d6ad6ab2179a |
| runs/Sep19_12-41-08_0ee812ae912a/events.out.tfevents.1789821668.0ee812ae912a.2917.1 | Other | 6.0 KB | 32311dced4b7 |
| runs/Sep19_12-42-00_0ee812ae912a/events.out.tfevents.1789821720.0ee812ae912a.2917.2 | Other | 6.0 KB | 1f3c7ade65ad |
| runs/Sep19_12-43-00_0ee812ae912a/events.out.tfevents.1789821780.0ee812ae912a.2917.3 | Other | 6.0 KB | e30669b9ad05 |
| runs/Sep19_12-43-58_0ee812ae912a/events.out.tfevents.1789821838.0ee812ae912a.2917.4 | Other | 6.0 KB | d6a2311db867 |
| runs/Sep19_12-47-09_0ee812ae912a/events.out.tfevents.1789822029.0ee812ae912a.2917.5 | Other | 88 B | a818c0848511 |
| runs/Sep19_17-38-21_0ad5d37f5105/events.out.tfevents.1789839501.0ad5d37f5105.8023.0 | Other | 7.3 KB | b3dece3e07ce |
| runs/Sep20_01-52-09_4a9f363499bc/events.out.tfevents.1789869131.4a9f363499bc.11169.0 | Other | 6.0 KB | f8e568f0ddf5 |
| runs/Sep20_01-53-40_4a9f363499bc/events.out.tfevents.1789869220.4a9f363499bc.11169.1 | Other | 6.0 KB | ac015d6b2d77 |
| runs/Sep20_01-55-22_4a9f363499bc/events.out.tfevents.1789869322.4a9f363499bc.11169.2 | Other | 7.5 KB | 971e5631a7f4 |
| runs/Sep20_02-21-47_4a9f363499bc/events.out.tfevents.1789870910.4a9f363499bc.11169.3 | Other | 6.0 KB | ff27ac7a2b4d |
| runs/Sep20_02-22-08_4a9f363499bc/events.out.tfevents.1789870928.4a9f363499bc.11169.4 | Other | 6.0 KB | 39175b2598d5 |
| runs/Sep20_02-22-39_4a9f363499bc/events.out.tfevents.1789870959.4a9f363499bc.11169.5 | Other | 6.0 KB | e29a7b9ecbc3 |
| runs/Sep20_02-23-53_4a9f363499bc/events.out.tfevents.1789871033.4a9f363499bc.11169.6 | Other | 6.9 KB | 8332b564e1c1 |
| runs/Sep20_02-37-03_4a9f363499bc/events.out.tfevents.1789871823.4a9f363499bc.11169.7 | Other | 6.9 KB | 7e39dfb72a1a |
| runs/Sep20_02-55-07_4a9f363499bc/events.out.tfevents.1789872907.4a9f363499bc.11169.8 | Other | 6.9 KB | e99ebb84f2ec |
| runs/Sep20_03-13-42_4a9f363499bc/events.out.tfevents.1789874022.4a9f363499bc.11169.9 | Other | 7.3 KB | bf4bb90edff3 |
| .gitattributes | Repository | 1.5 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 1.3 GB
Released by Ngo Hoang Huy 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 Wav2Vec_VinData_Full
How much GPU memory does Wav2Vec_VinData_Full need?
About 0.8 GB at 16-bit and 0.2 GB at 4-bit: the weights (316M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run Wav2Vec_VinData_Full 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.