Instructions to use galsenai/m2m100_lr_2e5_gradd_accum_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use galsenai/m2m100_lr_2e5_gradd_accum_2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("galsenai/m2m100_lr_2e5_gradd_accum_2") model = AutoModelForSeq2SeqLM.from_pretrained("galsenai/m2m100_lr_2e5_gradd_accum_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e62598e035143aac0bb9195a19329d0ee5ff1c75b10e3daaadaf7f6b6be0bb2e
- Size of remote file:
- 7.28 kB
- SHA256:
- c71c82d9a9a3cc2be119d32efc9e2317ea884bc7dcc01bbf52a7e78556857d2d
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