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:
# 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 pytorch_model.bin from Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64: direct link, hf CLI and curl.
- Browser
- Download file 2.49 GB
-
https://huggingface.co/Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Splend1dchan/wav2vec2-large-lv60_mt5lephone-small_textdecoderonly_bs64/resolve/main/pytorch_model.bin
2.49 GB
- Xet hash:
- fa45bd21cd0994966b7f6615ad409e13c8b5fba0638261c5865b1d09ff3cb04d
- Size of remote file:
- 2.49 GB
- SHA256:
- c6d213d156ccc265e0f67fc2f58a0629adce1981e14ebd920724e332872b3ae2
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