Instructions to use pere/multi-sentencefix-mt5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/multi-sentencefix-mt5-large with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="pere/multi-sentencefix-mt5-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pere/multi-sentencefix-mt5-large") model = AutoModelForSeq2SeqLM.from_pretrained("pere/multi-sentencefix-mt5-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c2e8799870aff379ecfee22975ba7b54626f6eb50fdf8c99c2527523d85b8e1
- Size of remote file:
- 4.92 GB
- SHA256:
- 97920dfc3dca92cbd770e6b1f13affa5d027fff90c9ffab94058e53128556ae0
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