Transformers
PyTorch
multilingual
seamless_language_pairs
audio
text
multimodal
seamless
subtitle-editing-time-prediction
translation-aware
language-pairs
Instructions to use videoloc/seamless-langpairs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use videoloc/seamless-langpairs with Transformers:
# Load model directly from transformers import HFSeamlessLanguagePairs model = HFSeamlessLanguagePairs.from_pretrained("videoloc/seamless-langpairs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7528991af3c68e5ab642c52e9db70514df18d32433ec558fae7863d6a308e82f
- Size of remote file:
- 4.86 GB
- SHA256:
- 7e3037a762e659d5e3acaf60ecdd58a76aea92fc01b50f1cb70fb200b802e2a6
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