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 pytorch_model.bin from masakhane/m2m100_418M_mos_fr_rel: direct link, hf CLI and curl.
- Browser
- Download file 1.94 GB
-
https://huggingface.co/masakhane/m2m100_418M_mos_fr_rel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://masakhane/m2m100_418M_mos_fr_rel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/masakhane/m2m100_418M_mos_fr_rel/resolve/main/pytorch_model.bin
1.94 GB
- Xet hash:
- 8bc471368ff27aecbb488bcbfee8349848f60890c810d8d881b05d1f6f2c9efb
- Size of remote file:
- 1.94 GB
- SHA256:
- b85e2db9c64f80e04653d97da688f87e30d13aa54ae79de894842b698099c3bb
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