Instructions to use daccuong2002/PhoBert-MultiLabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daccuong2002/PhoBert-MultiLabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="daccuong2002/PhoBert-MultiLabel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("daccuong2002/PhoBert-MultiLabel") model = AutoModelForSequenceClassification.from_pretrained("daccuong2002/PhoBert-MultiLabel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download bpe.codes from daccuong2002/PhoBert-MultiLabel: direct link, hf CLI and curl.
- Browser
- Download file 1.14 MB
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https://huggingface.co/daccuong2002/PhoBert-MultiLabel/resolve/main/bpe.codes
- Command line
-
hf download hf://daccuong2002/PhoBert-MultiLabel/bpe.codes
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curl -L -o bpe.codes https://huggingface.co/daccuong2002/PhoBert-MultiLabel/resolve/main/bpe.codes
1.14 MB
File too large to display, you can check the raw version instead.