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")# pip install -U transformers accelerate # 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
Download optimizer.pt from basilkr/Malasar_ASr_Final: direct link, hf CLI and curl.
- Browser
- Download file 6.11 GB
-
https://huggingface.co/basilkr/Malasar_ASr_Final/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://basilkr/Malasar_ASr_Final@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/basilkr/Malasar_ASr_Final/resolve/refs%2Fpr%2F1/optimizer.pt
6.11 GB
- Xet hash:
- 0aa6e7513788bce0923963271e840fd608be453ca0a7ed1c161772e8f40e70b1
- Size of remote file:
- 6.11 GB
- SHA256:
- 47ea4092ddde682d366002e26f501e8f2c43fa7a07916494a0a33eef1122e075
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