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 pytorch_model.bin from mgtoxd/machineLearningCourse: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/mgtoxd/machineLearningCourse/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://mgtoxd/machineLearningCourse@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mgtoxd/machineLearningCourse/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.26 GB
- Xet hash:
- e6725a55c0fb20b65d5d5575905cdc7c5811060f9290a7773b576c26354699a4
- Size of remote file:
- 1.26 GB
- SHA256:
- 00b604cf4d28e86559e8adaeb3a186daa89dc37f5ab216771a0a15a26db0de9f
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