Instructions to use xraychen/mqa-sim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xraychen/mqa-sim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="xraychen/mqa-sim")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("xraychen/mqa-sim") model = AutoModelForQuestionAnswering.from_pretrained("xraychen/mqa-sim") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9b218c49b75d641081eff2f8d61dddf6aca5e893653877b6ac127738c42db20
- Size of remote file:
- 436 MB
- SHA256:
- b28e31d0557a0212ecdb1e292992bd823eefd7bfa9663b0a54ec7b8042348f8d
路
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