dbiir/UER-py
Open-source PyTorch toolkit for pre-training and fine-tuning transformer-based language models with a model zoo.
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UER-py (Universal Encoder Representations) is an open-source toolkit for pre-training language models on general-domain corpora and fine-tuning on downstream NLP tasks. It provides modular implementations of major transformer architectures including BERT, GPT, GPT-2, RoBERTa, ALBERT, T5, BART, ELMO, and XLM-RoBERTa. The project includes a comprehensive model zoo with pre-trained models and supports tasks such as text classification and named entity recognition.
Frequently asked
- What is dbiir/UER-py?
- Open-source PyTorch toolkit for pre-training and fine-tuning transformer-based language models with a model zoo.
- Is UER-py open source?
- Yes — dbiir/UER-py is open source, released under the Apache-2.0 license.
- What language is UER-py written in?
- dbiir/UER-py is primarily written in Python.
- How popular is UER-py?
- dbiir/UER-py has 3.1k stars on GitHub.
- Where can I find UER-py?
- dbiir/UER-py is on GitHub at https://github.com/dbiir/UER-py.