Instructions to use luel/SeamlessM4T-lr-tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use luel/SeamlessM4T-lr-tmp with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/seamless-m4t-v2-large") model = PeftModel.from_pretrained(base_model, "luel/SeamlessM4T-lr-tmp") - Transformers
How to use luel/SeamlessM4T-lr-tmp with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("luel/SeamlessM4T-lr-tmp", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a563bc73d47aeb2774355714aa93e95d3833ef63b59e77ea6d9d520a3d8c3360
- Size of remote file:
- 31.2 MB
- SHA256:
- bb08273b3ab8f38ebcb33558f96257ef97beeb0441f8a28eb886ae71d9f3e1fa
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