Instructions to use tau/splinter-large-qass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tau/splinter-large-qass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tau/splinter-large-qass")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tau/splinter-large-qass") model = AutoModelForQuestionAnswering.from_pretrained("tau/splinter-large-qass") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ba4b2fb20ed7cb7c3d96c74a192c7c6a1da5ffbde86ba8f28935d2c7e48651a
- Size of remote file:
- 1.36 GB
- SHA256:
- 64d068da43fe35a6af32a4384008ca2298b044c2a7c1a24ec0b57a784912c3d8
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