Instructions to use dnnsdunca/agentic-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use dnnsdunca/agentic-Transformer with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("dnnsdunca/agentic-Transformer", set_active=True) - Notebooks
- Google Colab
- Kaggle
| transformers==4.20.1 | |
| torch==1.12.0 | |
| pandas==1.4.2 | |
| git clone https://huggingface.co/google-bert/bert-base-uncased | |
| # Load model directly | |
| from transformers import AutoTokenizer, AutoModelForMaskedLM | |
| tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-uncased") | |
| model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-uncased") | |
| # Use a pipeline as a high-level helper | |
| from transformers import pipeline | |
| pipe = pipeline("fill-mask", model="google-bert/bert-base-uncased") |