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 language_model/head.cleaned.bin from lilitket/aspram: direct link, hf CLI and curl.
- Browser
- Download file 12.8 GB
-
https://huggingface.co/lilitket/aspram/resolve/main/language_model/head.cleaned.bin
- Command line
-
hf download hf://lilitket/aspram/language_model/head.cleaned.bin
-
curl -L -o head.cleaned.bin https://huggingface.co/lilitket/aspram/resolve/main/language_model/head.cleaned.bin
12.8 GB
- Xet hash:
- 07daf8ffe3c9736be91c9e0b185b9551e6099d852fa7d7b8871ab69eada31472
- Size of remote file:
- 12.8 GB
- SHA256:
- e0c484d5f1c063ea131aae9bf0089e2c37819a1c540962d597a3518a1c2717ea
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