| language: zh | |
| tags: | |
| - exbert | |
| license: apache-2.0 | |
| widget: | |
| - text: "女人做得越纯粹，皮肤和身材就越好" | |
| - text: "我喜欢篮球" | |
| # liam168/c4-zh-distilbert-base-uncased | |
| ## Model description | |
| 用 ["女性","体育","文学","校园"]4类数据训练的分类模型。 | |
| ## Overview | |
| - **Language model**: DistilBERT | |
| - **Model size**: 280M | |
| - **Language**: Chinese | |
| ## Example | |
| ```python | |
| >>> from transformers import DistilBertForSequenceClassification , AutoTokenizer, pipeline | |
| >>> model_name = "liam168/c4-zh-distilbert-base-uncased" | |
| >>> class_num = 4 | |
| >>> ts_texts = ["女人做得越纯粹，皮肤和身材就越好", "我喜欢篮球"] | |
| >>> model = DistilBertForSequenceClassification.from_pretrained(model_name, num_labels=class_num) | |
| >>> tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| >>> classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer) | |
| >>> classifier(ts_texts[0]) | |
| >>> classifier(ts_texts[1]) | |
| [{'label': 'Female', 'score': 0.9137857556343079}] | |
| [{'label': 'Sports', 'score': 0.8206522464752197}] | |
| ``` | |