Instructions to use igorktech/hier-bert-i3-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use igorktech/hier-bert-i3-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="igorktech/hier-bert-i3-mlm", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("igorktech/hier-bert-i3-mlm", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from igorktech/hier-bert-i3-mlm: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/igorktech/hier-bert-i3-mlm/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://igorktech/hier-bert-i3-mlm@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/igorktech/hier-bert-i3-mlm/resolve/refs%2Fpr%2F1/training_args.bin
4.09 kB
- Xet hash:
- c47a10f7fde8300a28a8bca54cb7428d82a7e9120e10a74944448c036be937f0
- Size of remote file:
- 4.09 kB
- SHA256:
- 7f59d599c000a9dae6029191418497a813544fa3e5341b3436c6c16ed3c299be
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.