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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a59a45c0446042116f16447cd3ec666ec25893a8e0cf1a9024ec2831d1e331a
- Size of remote file:
- 499 MB
- SHA256:
- 804ae88d8412644084a6b70a8c057722660132f1f2168bb672d2bb471ff091b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.