Instructions to use ROGRANMAR/PRUEBA5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ROGRANMAR/PRUEBA5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ROGRANMAR/PRUEBA5")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ROGRANMAR/PRUEBA5") model = AutoModelForCTC.from_pretrained("ROGRANMAR/PRUEBA5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ROGRANMAR/PRUEBA5: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/ROGRANMAR/PRUEBA5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ROGRANMAR/PRUEBA5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ROGRANMAR/PRUEBA5/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 655b292ce9ba2de0651b874c0ddf72f54e833856afbaa77db1e1961ce7a89abf
- Size of remote file:
- 378 MB
- SHA256:
- 3cb585e643d592cccf913f71eda7031864b4af76ad0cfac2066aae729f489fc3
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