Instructions to use FarmerlineML/w2v-bert-2.0_krio_startup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FarmerlineML/w2v-bert-2.0_krio_startup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="FarmerlineML/w2v-bert-2.0_krio_startup")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("FarmerlineML/w2v-bert-2.0_krio_startup") model = AutoModelForCTC.from_pretrained("FarmerlineML/w2v-bert-2.0_krio_startup") - Notebooks
- Google Colab
- Kaggle
| { | |
| "feature_extractor": { | |
| "feature_extractor_type": "SeamlessM4TFeatureExtractor", | |
| "feature_size": 80, | |
| "num_mel_bins": 80, | |
| "padding_side": "right", | |
| "padding_value": 1, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "stride": 2 | |
| }, | |
| "processor_class": "Wav2Vec2Processor" | |
| } | |