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
File size: 285 Bytes
83a2a41 | 1 | {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 256, "special_tokens_map_file": null, "name_or_path": "vinai/phobert-base", "tokenizer_class": "PhobertTokenizer"} |