Instructions to use masakhane/m2m100_418M_mos_fr_rel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use masakhane/m2m100_418M_mos_fr_rel with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("masakhane/m2m100_418M_mos_fr_rel") model = AutoModelForSeq2SeqLM.from_pretrained("masakhane/m2m100_418M_mos_fr_rel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from masakhane/m2m100_418M_mos_fr_rel: direct link, hf CLI and curl.
- Browser
- Download file 2.74 kB
-
https://huggingface.co/masakhane/m2m100_418M_mos_fr_rel/resolve/main/training_args.bin
- Command line
-
hf download hf://masakhane/m2m100_418M_mos_fr_rel/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/masakhane/m2m100_418M_mos_fr_rel/resolve/main/training_args.bin
2.74 kB
- Xet hash:
- e1dda020092eccff340480e3ef276f9d263b845fda9452bc4be263c39f060302
- Size of remote file:
- 2.74 kB
- SHA256:
- 709ffd182c16a615d4b3e53ae3a44faa700d48c2b7bfd03381773d571d0e7e68
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