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 # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="tau/splinter-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tau/splinter-base") model = AutoModelForQuestionAnswering.from_pretrained("tau/splinter-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tau/splinter-base: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/tau/splinter-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tau/splinter-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tau/splinter-base/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 0aa6001ba33e3dcffdfc57b3b50b1dee7b1c4130f19ca4b40f3abf28cb19d617
- Size of remote file:
- 431 MB
- SHA256:
- a519107f0c0ff71ab619c5dac6b9456d6a35159ad368e25effca13fc746ccf49
路
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