Instructions to use Lvxue/m2m100_ORT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lvxue/m2m100_ORT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Lvxue/m2m100_ORT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decoder_model.onnx from Lvxue/m2m100_ORT: direct link, hf CLI and curl.
- Browser
- Download file 1.86 GB
-
https://huggingface.co/Lvxue/m2m100_ORT/resolve/main/decoder_model.onnx
- Command line
-
hf download hf://Lvxue/m2m100_ORT/decoder_model.onnx
-
curl -L -o decoder_model.onnx https://huggingface.co/Lvxue/m2m100_ORT/resolve/main/decoder_model.onnx
1.86 GB
- Xet hash:
- 04ce67618188956150c234fb7cba9270978beb81291ba2388c4aba3105244e9a
- Size of remote file:
- 1.86 GB
- SHA256:
- 8685bd54ab2bcbd04b7d17a8e5286658f8555bbaee28258a1da9dbd32d49eccd
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