Instructions to use Rafaelrosendo1/my_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rafaelrosendo1/my_models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Rafaelrosendo1/my_models")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Rafaelrosendo1/my_models") model = AutoModelForSpeechSeq2Seq.from_pretrained("Rafaelrosendo1/my_models") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f764e88d54a5f7249435b8012632dcfde028df436f8465f83a0b761b16a3c1c0
- Size of remote file:
- 6.17 GB
- SHA256:
- efbc81cf57dd3a06f165edd8eff9f6d944afca58ca0f8d903996918ed7275638
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