Text Classification
Transformers
PyTorch
Chinese
bert
pretrain
environment
classification
topic classification
text-embeddings-inference
Instructions to use celtics1863/env-bert-topic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use celtics1863/env-bert-topic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="celtics1863/env-bert-topic")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("celtics1863/env-bert-topic") model = AutoModelForSequenceClassification.from_pretrained("celtics1863/env-bert-topic") - Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null,"tokenizer_class": "BertTokenizer"} |