Automatic Speech Recognition
Transformers
Safetensors
Northern Kurdish
wav2vec2-bert
kurdish
badini
kurmanji
low-resource
Instructions to use computeram/badini-w2v-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use computeram/badini-w2v-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="computeram/badini-w2v-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("computeram/badini-w2v-bert") model = AutoModelForCTC.from_pretrained("computeram/badini-w2v-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
melhum commited on
Delete processor_config.json with huggingface_hub
Browse files- processor_config.json +0 -13
processor_config.json
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{
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"feature_extractor": {
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"feature_extractor_type": "SeamlessM4TFeatureExtractor",
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"feature_size": 80,
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"num_mel_bins": 80,
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"padding_side": "right",
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"padding_value": 1,
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"return_attention_mask": true,
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"sampling_rate": 16000,
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"stride": 2
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},
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"processor_class": "Wav2Vec2BertProcessor"
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}
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