Instructions to use mosesdaudu/DSN_ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mosesdaudu/DSN_ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mosesdaudu/DSN_ASR")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mosesdaudu/DSN_ASR") model = AutoModelForSpeechSeq2Seq.from_pretrained("mosesdaudu/DSN_ASR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mosesdaudu/DSN_ASR: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/mosesdaudu/DSN_ASR/resolve/main/training_args.bin
- Command line
-
hf download hf://mosesdaudu/DSN_ASR/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mosesdaudu/DSN_ASR/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- 360beac5dfa677c4092336ae4b0ee4d80b976f569fe144a42fa279866984d70a
- Size of remote file:
- 3.77 kB
- SHA256:
- 7e7cea8fcbccf14c016f1b0577214e0259201a5898261aa3b76f980387258331
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.