Instructions to use GioReg/notiBERTo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GioReg/notiBERTo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GioReg/notiBERTo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GioReg/notiBERTo") model = AutoModelForMaskedLM.from_pretrained("GioReg/notiBERTo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from GioReg/notiBERTo: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/GioReg/notiBERTo/resolve/main/training_args.bin
- Command line
-
hf download hf://GioReg/notiBERTo/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GioReg/notiBERTo/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 5d583f1e4d845ee41c87f26ad66372a5dfb55901018a74908a2364382edb4e89
- Size of remote file:
- 3.06 kB
- SHA256:
- be8d8159f2931e67966311a001e0474a4a40a31a6b9dad93f90261532e8407d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.