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:
- 7994b6d3c812909005a6a7489d1d8401553d7a331f7654d2478989edde2d4187
- Size of remote file:
- 4.14 kB
- SHA256:
- d18e336b3f5d8254483df0bd63898b0453afaf1ea6b44366916123925b7eabd8
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