Instructions to use Bainbridge/bert-incl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bainbridge/bert-incl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Bainbridge/bert-incl")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Bainbridge/bert-incl") model = AutoModelForSequenceClassification.from_pretrained("Bainbridge/bert-incl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Bainbridge/bert-incl: direct link, hf CLI and curl.
- Browser
- Download file 725 kB
-
https://huggingface.co/Bainbridge/bert-incl/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://Bainbridge/bert-incl@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Bainbridge/bert-incl/resolve/refs%2Fpr%2F1/tokenizer.json
725 kB
File too large to display, you can check the raw version instead.