Instructions to use PartAI/TookaBERT-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PartAI/TookaBERT-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PartAI/TookaBERT-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PartAI/TookaBERT-Base") model = AutoModelForMaskedLM.from_pretrained("PartAI/TookaBERT-Base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22d15647ef5cb723b4538284f3d37424e9d10a61a38bd0c2a9d081a0932b90b2
- Size of remote file:
- 492 MB
- SHA256:
- ae64f4775aec11c0a4d6dda69bcb60bff55faa3ee9d23c922988fa2a42240de4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.