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:
- 910a37945d1569e6f1c82c5494fbc574988c5e4a71690a9554f364b0ef62a0d5
- Size of remote file:
- 1.42 GB
- SHA256:
- cb5808eb38f5ac0aeff73eeb580c6893c4776f5bd0114f0531adcdf219c43f4c
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