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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e85b266d33e9326b5a2ad2f010223225ac7105e9aac29eb8d0d9e1292c13fe6
- Size of remote file:
- 16.3 MB
- SHA256:
- 93c3578052e1605d8332eb961bc08d72e246071974e4cc54aa6991826b802aa5
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