Instructions to use Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_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_mt5lephone-small_textdecoderonly_bs64 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import SpeechMixEEDT5 model = SpeechMixEEDT5.from_pretrained("Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64/resolve/main/training_args.bin
- Command line
-
hf download hf://Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- e1b333d11f345b2fd615e85a9ed75da8f17a7ba407afb9704dd689bbc02fd5db
- Size of remote file:
- 3.38 kB
- SHA256:
- 46ceb93faab410daca077c7e53628d737a08b160dd7492c11fcc713e46e571d2
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