Instructions to use mgtoxd/tsttst with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgtoxd/tsttst with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mgtoxd/tsttst")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mgtoxd/tsttst") model = AutoModelForCTC.from_pretrained("mgtoxd/tsttst", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from mgtoxd/tsttst: direct link, hf CLI and curl.
- Browser
- Download file 722 MB
-
https://huggingface.co/mgtoxd/tsttst/resolve/main/optimizer.pt
- Command line
-
hf download hf://mgtoxd/tsttst/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/mgtoxd/tsttst/resolve/main/optimizer.pt
722 MB
- Xet hash:
- 342962766aaeabfa3543bc8993df0fb308dd1acc43f5fcd7dca4d97fe2b06d14
- Size of remote file:
- 722 MB
- SHA256:
- bb68bd928c8754c184cf5882a6e988da39c287f4ab5a5c6d3faee7f2ff7c44ef
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