Instructions to use devkyle/base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/base-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/base-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/base-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/base-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41363be37ce1f8b2dbfc877fd19e85461913db71002dba97e2ba937cf60dca5c
- Size of remote file:
- 290 MB
- SHA256:
- 24c85b8609ca14ddfda38b23307d4d655f0ab9d3afa31b9dd02a7cf9b5a96ffd
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