Instructions to use castorini/azbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/azbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="castorini/azbert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("castorini/azbert-base") model = AutoModelForPreTraining.from_pretrained("castorini/azbert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from castorini/azbert-base: direct link, hf CLI and curl.
- Browser
- Download file 530 kB
-
https://huggingface.co/castorini/azbert-base/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://castorini/azbert-base@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/castorini/azbert-base/resolve/refs%2Fpr%2F1/tokenizer.json
530 kB
File too large to display, you can check the raw version instead.