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 tokenizer_config.json from nqcccccc/phobert-multilabel-post-classification: direct link, hf CLI and curl.
- Browser
- Download file 285 Bytes
-
https://huggingface.co/nqcccccc/phobert-multilabel-post-classification/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://nqcccccc/phobert-multilabel-post-classification/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/nqcccccc/phobert-multilabel-post-classification/resolve/main/tokenizer_config.json
285 Bytes
| {"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"} |