Instructions to use anyspeech/clap-ipa-tiny-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anyspeech/clap-ipa-tiny-speech with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, SpeechEncoder processor = AutoProcessor.from_pretrained("anyspeech/clap-ipa-tiny-speech") model = SpeechEncoder.from_pretrained("anyspeech/clap-ipa-tiny-speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from anyspeech/clap-ipa-tiny-speech: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/anyspeech/clap-ipa-tiny-speech/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://anyspeech/clap-ipa-tiny-speech/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anyspeech/clap-ipa-tiny-speech/resolve/main/pytorch_model.bin
33.4 MB
- Xet hash:
- 557448eaf594bc323cb10980f1a5036b4ba55e9cb3ce0c21000a5c6e7df96e47
- Size of remote file:
- 33.4 MB
- SHA256:
- 2e08cccc116fc60b0f10a3fc3368b5ecef751b1cb063c70d86d8613a16c250ab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.