Instructions to use devkyle/base-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/base-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/base-v3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/base-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/base-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74666542bc114688832228ac27308f581ee3f7662b4b36442362ae7f305c99df
- Size of remote file:
- 290 MB
- SHA256:
- 3ac4565293df4ef8f4dd80f7cefd5a3bbb95231d97c26c27a0d7c4190f95d831
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