Instructions to use omarelsayeed/last with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarelsayeed/last with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="omarelsayeed/last")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("omarelsayeed/last") model = AutoModelForCTC.from_pretrained("omarelsayeed/last", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from omarelsayeed/last: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/omarelsayeed/last/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://omarelsayeed/last/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/omarelsayeed/last/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- a27ff9634fc39017c875836de5898b8bcd0da02a29aecc8ff346c35a32b53f9a
- Size of remote file:
- 1.26 GB
- SHA256:
- b18d26027ae4553d623f80900ea37a6828af517f3728ab15960a3bc189cb7f82
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