Instructions to use intelcomp/ipc_level1_D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level1_D with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level1_D")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level1_D") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level1_D") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a59be800be4a6918c89e88dd9bc47cb3c3cb149c9fb4be1a0faedc0313ccf7d8
- Size of remote file:
- 1.42 GB
- SHA256:
- ee448e4685ee86bdc0db721c5dfef5da853dd4a23c369ef90e43db7614d005dc
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