Instructions to use GeoffVdr/run_a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GeoffVdr/run_a with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GeoffVdr/run_a")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("GeoffVdr/run_a") model = AutoModelForSpeechSeq2Seq.from_pretrained("GeoffVdr/run_a", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from GeoffVdr/run_a: direct link, hf CLI and curl.
- Browser
- Download file 3.06 GB
-
https://huggingface.co/GeoffVdr/run_a/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://GeoffVdr/run_a@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/GeoffVdr/run_a/resolve/refs%2Fpr%2F1/pytorch_model.bin
3.06 GB
- Xet hash:
- 1fd76c4187a7a8df2a5a038613e0319fa4baeddc276dfa4096a5583fa952d30a
- Size of remote file:
- 3.06 GB
- SHA256:
- b63775e083a5ac3f7d21bdb9de29ee43f792d0346565b98ce39577c8cbc2acaa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.