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:
- e67a5bd44a3f61e413e79d2be67aab0d72710aedff6a00b1e41ab1879c71a8ba
- Size of remote file:
- 1.94 GB
- SHA256:
- 9a357c2dcb561269ba604ed1d579d97b426011db227b822a8e949809ce44ac6b
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