Instructions to use aieng-lab/codebert-base_requirement-completion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aieng-lab/codebert-base_requirement-completion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aieng-lab/codebert-base_requirement-completion")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aieng-lab/codebert-base_requirement-completion") model = AutoModelForMaskedLM.from_pretrained("aieng-lab/codebert-base_requirement-completion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1063fbfaf4036a4d8721e972c10bc34f48cadc43a42347951dfeb2e647c61f0
- Size of remote file:
- 249 MB
- SHA256:
- c3a4aa0babbfef717439e181cc59515e7b49b1a6d6b37dd11bd9fd70d3a492ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.