Instructions to use intelcomp/nace2_level1_26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_26 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_26")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_26") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_26") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0989a78720a5bddc23b1d18f855b9eb630d04a85793a436a692c3f955a824d62
- Size of remote file:
- 1.42 GB
- SHA256:
- 5c2e7b7cb4a44ca07738f0fc77ed553d09db0bdd88cec362f2b6f63fe3b8e76a
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