Instructions to use tau/splinter-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tau/splinter-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tau/splinter-base")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tau/splinter-base") model = AutoModelForQuestionAnswering.from_pretrained("tau/splinter-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0aa6001ba33e3dcffdfc57b3b50b1dee7b1c4130f19ca4b40f3abf28cb19d617
- Size of remote file:
- 431 MB
- SHA256:
- a519107f0c0ff71ab619c5dac6b9456d6a35159ad368e25effca13fc746ccf49
路
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