Instructions to use intelcomp/ipc_level1_B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level1_B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level1_B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level1_B") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level1_B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34bad4a59e5fd9d3909025f05ef1bc8081e02661fe0745ebf8f955af2d6c2368
- Size of remote file:
- 1.42 GB
- SHA256:
- 294172991118cb6c492cac05d949ead92a2f5a950e7559cec6850860222c05ee
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