Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Russian
gigaam-ctc
asr
gigaam
stt
ctc
audio
speech
custom_code
Instructions to use waveletdeboshir/gigaam-ctc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use waveletdeboshir/gigaam-ctc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="waveletdeboshir/gigaam-ctc", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("waveletdeboshir/gigaam-ctc", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 534 Bytes
4ec70b3 5069985 4ec70b3 5069985 4ec70b3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"chunk_length": 30,
"feature_extractor_type": "GigaAMFeatureExtractor",
"feature_extractor_class": "GigaAMFeatureExtractor",
"feature_size": 64,
"hop_length": 160,
"n_samples": 480000,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000,
"auto_map": {
"AutoFeatureExtractor": "gigaam_transformers.GigaAMFeatureExtractor",
"AutoProcessor": "gigaam_transformers.GigaAMProcessor"
},
"processor_class": "GigaAMProcessor",
"model_type": "gigaam-ctc"
}
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