Instructions to use kabir5297/BanglaASR-XLSR-SmallLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kabir5297/BanglaASR-XLSR-SmallLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kabir5297/BanglaASR-XLSR-SmallLM")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("kabir5297/BanglaASR-XLSR-SmallLM") model = AutoModelForCTC.from_pretrained("kabir5297/BanglaASR-XLSR-SmallLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa83b721f3e474715665be3b5ee4d6513b707d22061e1986a75a93b6702c8482
- Size of remote file:
- 1.26 GB
- SHA256:
- a47166c8a6d90a3de68f63c3058238262f1a53836436c265fc7b13e34e73f461
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.