Instructions to use iyaja/codebert-llvm-ic-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iyaja/codebert-llvm-ic-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iyaja/codebert-llvm-ic-v0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iyaja/codebert-llvm-ic-v0") model = AutoModelForSequenceClassification.from_pretrained("iyaja/codebert-llvm-ic-v0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 382c41277090f9365097aa1dc4206dc5ea71cd52de4dadbe12bd56368861af9e
- Size of remote file:
- 371 MB
- SHA256:
- 1dc3626dc19e9fed961536102db1ed027975158d6c04f06f6d5dd6008de3d88b
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