Instructions to use Codebee/Bert-FD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Codebee/Bert-FD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Codebee/Bert-FD")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Codebee/Bert-FD") model = AutoModelForMaskedLM.from_pretrained("Codebee/Bert-FD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49b7d1dd65a3fe7bea585c2cdc68c874d23c5a73652d694354652200a618ee72
- Size of remote file:
- 412 MB
- SHA256:
- 3404a1ffd8da507042e8161013ba2a4fc49858b4e3f8fbf5ce5724f94883aec3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.