Instructions to use basilkr/Malasar_ASr_Final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basilkr/Malasar_ASr_Final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="basilkr/Malasar_ASr_Final")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("basilkr/Malasar_ASr_Final") model = AutoModelForSpeechSeq2Seq.from_pretrained("basilkr/Malasar_ASr_Final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0aa6e7513788bce0923963271e840fd608be453ca0a7ed1c161772e8f40e70b1
- Size of remote file:
- 6.11 GB
- SHA256:
- 47ea4092ddde682d366002e26f501e8f2c43fa7a07916494a0a33eef1122e075
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