Instructions to use Splend1dchan/wav2vec2-large-lv60_mt5-base_textlna_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_textlna_bs64 with Transformers:
# Load model directly from transformers import SpeechMixEEDT5 model = SpeechMixEEDT5.from_pretrained("Splend1dchan/wav2vec2-large-lv60_mt5-base_textlna_bs64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eae1695f655c264dea472376938370f103640233d2898670444479a99606cd34
- Size of remote file:
- 3.62 GB
- SHA256:
- c007492e97a8f2585a23b1e71766a71a365a41697c1e158f53ba4ffdaf5ab7e4
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