Instructions to use anyspeech/ipa-seg-tiny-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anyspeech/ipa-seg-tiny-speech with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, SpeechEncoder processor = AutoProcessor.from_pretrained("anyspeech/ipa-seg-tiny-speech") model = SpeechEncoder.from_pretrained("anyspeech/ipa-seg-tiny-speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from anyspeech/ipa-seg-tiny-speech: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/anyspeech/ipa-seg-tiny-speech/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://anyspeech/ipa-seg-tiny-speech/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anyspeech/ipa-seg-tiny-speech/resolve/main/pytorch_model.bin
33.4 MB
- Xet hash:
- a7023dc9a8e6bc8586369ef7816b39306baaacae42d90185c3cf8eec7b6fdd14
- Size of remote file:
- 33.4 MB
- SHA256:
- 1e20ac99d2a14ba3f35b735e5e723cde879f10f014b7243153f4dd8d5576568a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.