Instructions to use natmin322/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use natmin322/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="natmin322/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("natmin322/model") model = AutoModelForCTC.from_pretrained("natmin322/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from natmin322/model: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/natmin322/model/resolve/main/training_args.bin
- Command line
-
hf download hf://natmin322/model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/natmin322/model/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- df7d7f2306739db5e3a01f61f37b297cbc7a5115cd4c88768d0bf3b5732f254a
- Size of remote file:
- 3.31 kB
- SHA256:
- c77202772e0fb2bd53b6b609cffede63a312b8754d0669078569da8bdb590eba
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