Instructions to use intelcomp/ipc_level1_C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level1_C with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level1_C")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level1_C") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level1_C") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23776f1aee5107f6b44fb9370dcdd2d717350579a2727cf5b71df7acd2da864a
- Size of remote file:
- 1.42 GB
- SHA256:
- 3eb0f3601af13bca7e3d72cae8ef25b775502b0155e89746e28ee95c940ef299
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