Instructions to use jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_validation.json from jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729: direct link, hf CLI and curl.
- Browser
- Download file 13.9 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729/resolve/main/transcriptions_cv7_validation.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729/transcriptions_cv7_validation.json
-
curl -L -o transcriptions_cv7_validation.json https://huggingface.co/jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729/resolve/main/transcriptions_cv7_validation.json
13.9 MB
- Xet hash:
- 0a199385bc87ccb657b65f890e0e8f04d0bcc4a898e720092210d59dead85713
- Size of remote file:
- 13.9 MB
- SHA256:
- 833d6fd6ee27a761bbbcee20eab42f29ec3156113c0483972b8a1d9f3743ddfc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.