Text Classification
Transformers
PyTorch
Chinese
bert
environment
multi-class
classification
text-embeddings-inference
Instructions to use celtics1863/env-bert-cls-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use celtics1863/env-bert-cls-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="celtics1863/env-bert-cls-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("celtics1863/env-bert-cls-chinese") model = AutoModelForSequenceClassification.from_pretrained("celtics1863/env-bert-cls-chinese") - Notebooks
- Google Colab
- Kaggle
中文环境文本分类模型,1.6M的数据集,在env-bert-chinese上进行fine-tuning。
分为环境影响评价与控制、碳排放控制、水污染控制、大气污染控制、土壤污染控制、环境生态、固体废物、环境毒理与健康、环境微生物、环境政策与经济10类。
项目正在进行中,后续会陆续更新相关内容。
清华大学环境学院课题组
有相关需求、建议,联系bi.huaibin@foxmail.com
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