Fill-Mask
Transformers
PyTorch
Vietnamese
xlm-roberta
Vietnamese
Social Media
Vietnamese Pre-trained Model
Sentiment Analysis
Hate Speech Detection
Spam Detection
Emotionn Recognition
Instructions to use uitnlp/visobert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uitnlp/visobert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uitnlp/visobert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uitnlp/visobert") model = AutoModelForMaskedLM.from_pretrained("uitnlp/visobert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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# <a name="introduction"></a> ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing (EMNLP 2023 - Main)
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**Disclaimer**: The paper contains actual comments on social networks that might be construed as abusive, offensive, or obscene.
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- text: "hào quang rực <mask>"
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# <a name="introduction"></a> ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing (EMNLP 2023 - Main)
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**Disclaimer**: The paper contains actual comments on social networks that might be construed as abusive, offensive, or obscene.
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