Instructions to use MickyMike/codebert-c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MickyMike/codebert-c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MickyMike/codebert-c")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MickyMike/codebert-c") model = AutoModelForMaskedLM.from_pretrained("MickyMike/codebert-c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc8310f11d264b9e5eadab576064f796cc5a3b3343519502cf5b17e2da5d1c5c
- Size of remote file:
- 499 MB
- SHA256:
- c429335c923f8dc00e02a8c17485a9806a30c42c7d474b6368d18f8200d7d9d3
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