Instructions to use frett/chinese_extract_lert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_lert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_lert")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_lert") model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_lert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97539f1cbb2ab75e8e61e5b3ad9704b64a57fc45cc6e895110e816e812e414c8
- Size of remote file:
- 407 MB
- SHA256:
- 341ea766059745d515d3009ebf33b521175887bfb3fdb145d130ecb36e62b17f
路
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