Text Classification
Transformers
PyTorch
TensorBoard
Vietnamese
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ndbao2002/bert-base-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ndbao2002/bert-base-vi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ndbao2002/bert-base-vi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ndbao2002/bert-base-vi") model = AutoModelForSequenceClassification.from_pretrained("ndbao2002/bert-base-vi") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- vietnamese_students_feedback
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model-index:
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- name: bert-base-vi
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results: []
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language:
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- vi
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pipeline_tag: text-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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language:
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- vi
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- vietnamese_students_feedback
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pipeline_tag: text-classification
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base_model: bert-base-uncased
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model-index:
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- name: bert-base-vi
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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