Instructions to use sid321axn/M2M101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sid321axn/M2M101 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sid321axn/M2M101") model = AutoModelForSeq2SeqLM.from_pretrained("sid321axn/M2M101", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sid321axn/M2M101: direct link, hf CLI and curl.
- Browser
- Download file 3.71 kB
-
https://huggingface.co/sid321axn/M2M101/resolve/main/training_args.bin
- Command line
-
hf download hf://sid321axn/M2M101/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sid321axn/M2M101/resolve/main/training_args.bin
3.71 kB
- Xet hash:
- 6808d2d661d1420fce873abea71d6cbce00f340e9e56db93b6c33f85c0c77c43
- Size of remote file:
- 3.71 kB
- SHA256:
- a89b2620496061d77a1821e9e564e6b43719f861ec5fffeac67c350c43c7e01e
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