Instructions to use lilitket/aspram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lilitket/aspram with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lilitket/aspram")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lilitket/aspram") model = AutoModelForCTC.from_pretrained("lilitket/aspram", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from lilitket/aspram: direct link, hf CLI and curl.
- Browser
- Download file 8.64 GB
-
https://huggingface.co/lilitket/aspram/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://lilitket/aspram/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/lilitket/aspram/resolve/main/pytorch_model.bin
8.64 GB
- Xet hash:
- 1ce03e0c51fb10eb947c0eedce50feacc612d23a5b8f0ff2ac3a6c72d5398c92
- Size of remote file:
- 8.64 GB
- SHA256:
- c77a71fd7a47d3c5b4711380f3a4c079cb87da2c3bec60dba23bbc4f62f27842
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