Instructions to use tau/splinter-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tau/splinter-large 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-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tau/splinter-large") model = AutoModelForQuestionAnswering.from_pretrained("tau/splinter-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tau/splinter-large: direct link, hf CLI and curl.
- Browser
- Download file 1.33 GB
-
https://huggingface.co/tau/splinter-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tau/splinter-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tau/splinter-large/resolve/main/pytorch_model.bin
1.33 GB
- Xet hash:
- f0daf66158a204ea112c0cbd7fa20ae4fbb2b3bb4e58186b6d54658437a38932
- Size of remote file:
- 1.33 GB
- SHA256:
- a63b5206769b8f69b233b04dac5fb65f6ccbc3c5c414339f8dea6dad3a95c12d
路
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