Instructions to use Drahokma/whisper-large-v3-LORA-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Drahokma/whisper-large-v3-LORA-colab with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Drahokma/whisper-large-v3-LORA-colab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a949f0dc91ebc008fd0543440d3230e917d4eb220a95bc619d1a877c7625e57b
- Size of remote file:
- 63 MB
- SHA256:
- 9bb2eab641e67984028e6243a90fbd913f34e067901a4b046a4a8e3181d26b2c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.