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:
- d42d775f53f3b951a0e20a3035008e44b9235cbfbc954a89b56189cab271258e
- Size of remote file:
- 5.37 kB
- SHA256:
- 75e23993827d880453c4a612c57de64c8a75ef26fc5ae06500432afbc5c69b2c
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