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:
- 41b0205b9e3d237ce9f35169c7fb0001b4f5f28669ebb8bafb867e3d71d5054e
- Size of remote file:
- 353 MB
- SHA256:
- b38427068662252efba8db7cc2a61edb8dacdd6abc8adeaffb7044243bf6acdf
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