Instructions to use kien-vu-uet/cross-encoder-mt5-base-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kien-vu-uet/cross-encoder-mt5-base-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kien-vu-uet/cross-encoder-mt5-base-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kien-vu-uet/cross-encoder-mt5-base-finetuned") model = AutoModelForSequenceClassification.from_pretrained("kien-vu-uet/cross-encoder-mt5-base-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 224e79b4bb8620eb2aa74e16757a7815b8d1f916f1af390091667359b2b1edeb
- Size of remote file:
- 5.24 kB
- SHA256:
- d659d3d28e3db31de573b99bfaf0eeaba45070fe7d4a73fb1c0a93f0a9099552
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