Text Classification
Transformers
Safetensors
Vietnamese
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use PB3002/ViNMeDicalQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PB3002/ViNMeDicalQA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PB3002/ViNMeDicalQA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PB3002/ViNMeDicalQA") model = AutoModelForSequenceClassification.from_pretrained("PB3002/ViNMeDicalQA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f47394972c92ca06021d4ef53cccf4bee2b8adbf68239eeca02ca679a8c2841
- Size of remote file:
- 17.1 MB
- SHA256:
- 890ca36ac0cbf179c0d82c7e87b5a968b933d218f075364e242612e896826108
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