Instructions to use devkyle/small-v11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/small-v11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/small-v11")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/small-v11") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/small-v11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94f20f9be0651b47575322e8a20793733a38ee9535577491b0103f0aca749fed
- Size of remote file:
- 5.56 kB
- SHA256:
- a0b09c8cd7d6440f60f73836d59b6ac52aaf8a10d188cc86e2c10a985183690f
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