Instructions to use mrm8488/ManuERT-for-xqua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/ManuERT-for-xqua with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/ManuERT-for-xqua")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/ManuERT-for-xqua") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/ManuERT-for-xqua") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 619bef8b9f22f0465b955d257d9d420463308e07120dffe464c7bbb811fc5a3a
- Size of remote file:
- 709 MB
- SHA256:
- 674c7330da1e5a43f87582b4bac5e64990e85cfc2876ba5667726f921d7810b1
路
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