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