Automatic Speech Recognition
Transformers
Safetensors
Twi
Akan
whisper
akan
twi
ghanaian-speech-lab
serendepify-gsl
Instructions to use teckedd/serendepify-gsl-asr-ak-waxal-gnlp-whisper-small-broad-lowlr-freezeenc-fullft-v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use teckedd/serendepify-gsl-asr-ak-waxal-gnlp-whisper-small-broad-lowlr-freezeenc-fullft-v0.3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="teckedd/serendepify-gsl-asr-ak-waxal-gnlp-whisper-small-broad-lowlr-freezeenc-fullft-v0.3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("teckedd/serendepify-gsl-asr-ak-waxal-gnlp-whisper-small-broad-lowlr-freezeenc-fullft-v0.3") model = AutoModelForSpeechSeq2Seq.from_pretrained("teckedd/serendepify-gsl-asr-ak-waxal-gnlp-whisper-small-broad-lowlr-freezeenc-fullft-v0.3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
serendepify-gsl-asr-ak-waxal-gnlp-whisper-small-broad-lowlr-freezeenc-fullft-v0.3 / preprocessor_config.json
| { | |
| "chunk_length": 30, | |
| "dither": 0.0, | |
| "feature_extractor_type": "WhisperFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 160, | |
| "n_fft": 400, | |
| "n_samples": 480000, | |
| "nb_max_frames": 3000, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "WhisperProcessor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |