Instructions to use uer/roberta-base-chinese-extractive-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uer/roberta-base-chinese-extractive-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="uer/roberta-base-chinese-extractive-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("uer/roberta-base-chinese-extractive-qa") model = AutoModelForQuestionAnswering.from_pretrained("uer/roberta-base-chinese-extractive-qa") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 264aea3b2bcd3b05a166c9e8a4870578edde3678c98a7957d4aa767d163d441b
- Size of remote file:
- 407 MB
- SHA256:
- a377de249a3b9c73702f3a3f7a2d2a0edca5ba5a65cf7a699594823e8a57a701
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