Instructions to use patricklai14/tapt_citation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patricklai14/tapt_citation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="patricklai14/tapt_citation")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("patricklai14/tapt_citation") model = AutoModelForMaskedLM.from_pretrained("patricklai14/tapt_citation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from patricklai14/tapt_citation: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/patricklai14/tapt_citation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://patricklai14/tapt_citation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/patricklai14/tapt_citation/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 2b653e38345396e5fb9ec2d675f622358e4d6927acb8d11837a7a69ceaae23a5
- Size of remote file:
- 499 MB
- SHA256:
- 112b3f50f06714e00e09f02adfb5ccd7a6a471559aca42a5cecf9f73f59114ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.