Instructions to use intelcomp/nace2_level1_42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_42")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_42") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_42") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc9a48a533bce66d217c54ee780c12e1d3e370af4c9fb45f752fc4e6fa1582a7
- Size of remote file:
- 1.42 GB
- SHA256:
- 634b318884f8b6934c3d16a4cf1acf2a30ee32b661341b59be729365ca780d45
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