Instructions to use devkyle/base-v2-dp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/base-v2-dp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/base-v2-dp")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/base-v2-dp") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/base-v2-dp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b60e49084aba7bc369d00cf523eeb87ba2a47730b23439c84574ab2a59d22947
- Size of remote file:
- 290 MB
- SHA256:
- 61b722ee8f25b02f7d6d179f87dc11bdb6333ae87593aab4a8e28a75abd6aef0
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