Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Russian
gigaam-ctc
asr
gigaam
stt
ctc
audio
speech
custom_code
Instructions to use Den4ikAI/gigaam-ctc-whisperx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Den4ikAI/gigaam-ctc-whisperx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Den4ikAI/gigaam-ctc-whisperx", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Den4ikAI/gigaam-ctc-whisperx", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 857ee1c61a06ed395c7dbb8f266f915af48d4eb4efb62a506fa5c328cfbd3874
- Size of remote file:
- 465 MB
- SHA256:
- 839d58a94da1153dbd7df3913ffcbef79e78b2c158636a323981c6dacb9eb320
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