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 model.safetensors from mgtoxd/machineLearningCourse: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/mgtoxd/machineLearningCourse/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://mgtoxd/machineLearningCourse@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/mgtoxd/machineLearningCourse/resolve/refs%2Fpr%2F1/model.safetensors
1.26 GB
- Xet hash:
- f04363fbe296563a60f913ccb34f4805707d928e74381b4f163ca5b6a3594a36
- Size of remote file:
- 1.26 GB
- SHA256:
- c538779776c30dfe6f0ece064979f47f096f170e390c2b5d521e3b2ef8e9aadc
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