Instructions to use Isaacp/bert-base-uncased-issues-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isaacp/bert-base-uncased-issues-128 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Isaacp/bert-base-uncased-issues-128")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Isaacp/bert-base-uncased-issues-128") model = AutoModelForMaskedLM.from_pretrained("Isaacp/bert-base-uncased-issues-128") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2 opened over 1 year ago
by
SFconvertbot
Librarian Bot: Add base_model information to model
#1 opened over 2 years ago
by
librarian-bot