Instructions to use Vkt/first_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vkt/first_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Vkt/first_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Vkt/first_model") model = AutoModelForCTC.from_pretrained("Vkt/first_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Vkt/first_model: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Vkt/first_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Vkt/first_model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Vkt/first_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.26 GB
- Xet hash:
- 4f971ae35da26992b9f2e8a3d84947a5021abda0534836141fba6d6d15c81882
- Size of remote file:
- 1.26 GB
- SHA256:
- eca7eb5c9147d26f8b22adc220d184b151a328104e5b077cf881f05736700af0
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