Instructions to use Splend1dchan/wav2vec2-large-lv60_mt5-base_textdecoderonly_bs64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Splend1dchan/wav2vec2-large-lv60_mt5-base_textdecoderonly_bs64 with Transformers:
# Load model directly from transformers import SpeechMixEEDT5 model = SpeechMixEEDT5.from_pretrained("Splend1dchan/wav2vec2-large-lv60_mt5-base_textdecoderonly_bs64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de86d0aa4c320dc1a3cdf0e86ea312c714e174d19e47c9d4757d8eca92b4f1d4
- Size of remote file:
- 3.62 GB
- SHA256:
- ec2755bf5e79f41a429745b971644f248b9ee55b4564b85182a4c3fa5a624bf2
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