Instructions to use mgtoxd/machineLearningCourse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgtoxd/machineLearningCourse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mgtoxd/machineLearningCourse")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mgtoxd/machineLearningCourse") model = AutoModelForCTC.from_pretrained("mgtoxd/machineLearningCourse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from mgtoxd/machineLearningCourse: direct link, hf CLI and curl.
- Browser
- Download file 623 Bytes
-
https://huggingface.co/mgtoxd/machineLearningCourse/resolve/refs%2Fpr%2F1/scheduler.pt
- Command line
-
hf download hf://mgtoxd/machineLearningCourse@refs/pr/1/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/mgtoxd/machineLearningCourse/resolve/refs%2Fpr%2F1/scheduler.pt
623 Bytes
- Xet hash:
- 83e2a1eaa660945503c4efe7d1f5369cb1b90e7822644328e42aa024690e1d5b
- Size of remote file:
- 623 Bytes
- SHA256:
- 4ffec80af644b58242768aec89d26ef0a97999a12561e3f4e5a27ef80389fbca
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