Instructions to use tau/splinter-base-qass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tau/splinter-base-qass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tau/splinter-base-qass")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tau/splinter-base-qass") model = AutoModelForQuestionAnswering.from_pretrained("tau/splinter-base-qass") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f687c681efa6e0fa36b6da72fcd010a0b988495fd422612f858ea6322e75b839
- Size of remote file:
- 445 MB
- SHA256:
- 523c9a0a37b9784592a310d65746291a75b6e66649585de9daad00322919ecaf
路
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