Instructions to use Akashpb13/ailabs_proj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akashpb13/ailabs_proj with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Akashpb13/ailabs_proj")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Akashpb13/ailabs_proj") model = AutoModelForCTC.from_pretrained("Akashpb13/ailabs_proj", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Akashpb13/ailabs_proj: direct link, hf CLI and curl.
- Browser
- Download file 2.49 GB
-
https://huggingface.co/Akashpb13/ailabs_proj/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://Akashpb13/ailabs_proj@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Akashpb13/ailabs_proj/resolve/refs%2Fpr%2F1/optimizer.pt
2.49 GB
- Xet hash:
- 680fedbceb89795de68086c192a32fcfb11d4fd44353c3571858b04ea510f664
- Size of remote file:
- 2.49 GB
- SHA256:
- 1dc734c1a4dd627199f36475e76ae0214cf217b24190577178226f4a8bf78b38
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