Instructions to use Python/ACROSS-m2o-eng-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Python/ACROSS-m2o-eng-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Python/ACROSS-m2o-eng-base") model = AutoModelForSeq2SeqLM.from_pretrained("Python/ACROSS-m2o-eng-base") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
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scheduler.pt filter=lfs diff=lfs merge=lfs -text
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spiece.model filter=lfs diff=lfs merge=lfs -text
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training_args.bin filter=lfs diff=lfs merge=lfs -text
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scheduler.pt filter=lfs diff=lfs merge=lfs -text
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spiece.model filter=lfs diff=lfs merge=lfs -text
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training_args.bin filter=lfs diff=lfs merge=lfs -text
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model.safetensors filter=lfs diff=lfs merge=lfs -text
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:0a5fbfe843951e5b9fb06740d6b6a36dcfc11de228059165d9956e675c2be64f
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size 2329638768
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