Instructions to use HamdanXI/bert-base-paradetox-editOps-preprocess with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HamdanXI/bert-base-paradetox-editOps-preprocess with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HamdanXI/bert-base-paradetox-editOps-preprocess")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HamdanXI/bert-base-paradetox-editOps-preprocess") model = AutoModelForMaskedLM.from_pretrained("HamdanXI/bert-base-paradetox-editOps-preprocess", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HamdanXI/bert-base-paradetox-editOps-preprocess: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/HamdanXI/bert-base-paradetox-editOps-preprocess/resolve/main/training_args.bin
- Command line
-
hf download hf://HamdanXI/bert-base-paradetox-editOps-preprocess/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HamdanXI/bert-base-paradetox-editOps-preprocess/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- cccdda38ac30fd22b6bc5e064c41853a09c8c650caee89728103b3159fdf625d
- Size of remote file:
- 4.6 kB
- SHA256:
- b30b4b7bd68f75e914afa2fcac910d0c3325d78c13ec9002d10f0456cb12d14b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.