# wav2vec-lt-lite
## Usage
The model can be used directly (without a language model) as follows:
```python
import torch
import torchaudio
from datasets import load_dataset
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
test_dataset = load_dataset("common_voice", "lt", split="test[:2%]") 
processor = Wav2Vec2Processor.from_pretrained("seccily/wav2vec-lt-lite")
model = Wav2Vec2ForCTC.from_pretrained("seccily/wav2vec-lt-lite")
resampler = torchaudio.transforms.Resample(48_000, 16_000)
```
Test Result: 59.47
{"language": "lt", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech"], "datasets": ["common_voice"], "metrics": ["wer"]}
transformers pytorch wav2vec2 automatic-speech-recognition audio speech lt dataset:common_voice license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #lt #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 

# wav2vec-lt-lite
## Usage
The model can be used directly (without a language model) as follows:

Test Result: 59.47
# wav2vec-lt-lite ## Usage
The model can be used directly (without a language model) as follows:

Test Result: 59.47
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #lt #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
 # wav2vec-lt-lite ## Usage
The model can be used directly (without a language model) as follows:

Test Result: 59.47
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #lt #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
# wav2vec-lt-lite## Usage
The model can be used directly (without a language model) as follows:

Test Result: 59.47