Instructions to use q-future/q-align-pcqa-sjtu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use q-future/q-align-pcqa-sjtu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="q-future/q-align-pcqa-sjtu", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("q-future/q-align-pcqa-sjtu", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ab4c6a728274ef73a05fd32bfe7845276b6315b8ccc7da85f3a8838e2519a62
- Size of remote file:
- 6.14 kB
- SHA256:
- d9027122f3e9b52b96789b463d0ec5dbf5188d24c21b651057d61b637230e20e
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