Model reference · open weights
wav2vec2-xlsr-53-ft-cy-en is an open-weight audio or speech model from techiaith. wav2vec2-xlsr-53-ft-cy-en (FP32) weighs 631 MB; the smallest configuration that runs it is RTX 3060 12 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the techiaith/wav2vec2-xlsr-53-ft-cy-en model card, 2026-10-01
What it is
| Released by | techiaith |
|---|---|
| Released | 2022-10-24 |
| Parameters | 315M |
| VRAM | 631 MB for the weights |
What it runs on
| Card | One stream | Memory |
|---|---|---|
| RTX 3060 12 GB | fits | 11.6 GB |
| RTX 4060 Ti 16 GB | fits | 15.4 GB |
| RTX 3090 24 GB | fits | 23.4 GB |
| RTX 4090 24 GB | fits | 23.4 GB |
| RTX 5090 32 GB | fits | 31.0 GB |
| L40S 48 GB | fits | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
An acoustic encoder model for Welsh and English speech recognition, fine-tuned from facebook/wav2vec2-large-xlsr-53 using transcribed spontaneous speech from techiaith/banc-trawsgrifiadau-bangor (v24.01) as well as Welsh and English speech data derived from version 16.1 the Common Voice datasets techiaith/commonvoice_16_1_en_cy
The wav2vec2-xlsr-ft-cy-en model can be used directly as follows:
import torch
import torchaudio
import librosa
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
processor = Wav2Vec2Processor.from_pretrained("techiaith/wav2vec2-xlsr-ft-cy-en")
model = Wav2Vec2ForCTC.from_pretrained("techiaith/wav2vec2-xlsr-ft-cy-en")
audio, rate = librosa.load(audio_file, sr=16000)
inputs = processor(audio, sampling_rate=16_000, return_tensors="pt", padding=True)
with torch.no_grad():
tlogits = model(inputs.input_values, attention_mask=inputs.attention_mask).logits
# greedy decoding
predicted_ids = torch.argmax(logits, dim=-1)
print("Prediction:", processor.batch_decode(predicted_ids))
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.