Instructions to use microsoft/codebert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/codebert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/codebert-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/codebert-base") model = AutoModel.from_pretrained("microsoft/codebert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Semantic clarity with MarCognity-AI and CodeBERT
#10
by elly99 - opened
CodeBERT understands code.MarCognity-AI asks: what makes code narrate thought?It’s a semantic cartographer:
– Maps intention vs syntax
– Scores cognitive clarity
– Reflects on the ethics of generation
Not just code. Code with cognition.
Explore the model — but more than that, I’d love to hear how others interpret “semantic clarity” in code.
Can a model truly reflect intention?
elly99 changed discussion title from MarCognity-AI for CodeBERT to Semantic clarity with MarCognity-AI and CodeBERT