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:
- ca650825f63c5d35c58a6753f2d400478fd7c34fe85fe2dba846a95ecee65c0e
- Size of remote file:
- 4.22 kB
- SHA256:
- 692e6d602c147051833fcc9a8ace0bfd086460b200a7fd9507d9f7723f100835
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