Token Classification
Transformers
TensorBoard
Safetensors
Vietnamese
electra
text-generation-inference
Instructions to use ChanBeDu/vivtb_electra-based_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChanBeDu/vivtb_electra-based_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ChanBeDu/vivtb_electra-based_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ChanBeDu/vivtb_electra-based_model") model = AutoModelForTokenClassification.from_pretrained("ChanBeDu/vivtb_electra-based_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ChanBeDu/vivtb_electra-based_model: direct link, hf CLI and curl.
- Browser
- Download file 468 Bytes
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https://huggingface.co/ChanBeDu/vivtb_electra-based_model/resolve/main/README.md
- Command line
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hf download hf://ChanBeDu/vivtb_electra-based_model/README.md
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curl -L -o README.md https://huggingface.co/ChanBeDu/vivtb_electra-based_model/resolve/main/README.md
468 Bytes
metadata
datasets:
- universal-dependencies/universal_dependencies
language:
- vi
metrics:
- accuracy
- f1
- precision
- recall
library_name: transformers
pipeline_tag: token-classification
tags:
- text-generation-inference
Overview: This model is finetuned based on NlpHUST vietnamese electra based model. The used datased is Universial dependencies dataset. Only the tree branch vi_vtb of the dataset is used for finetuning. The model is used for UPOS tagging task