Instructions to use intelcomp/nace2_level1_29 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_29 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_29")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_29") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_29") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4abea18d5850bea7cdc57d1656e0c3dd778c24f96e7dc48cc53e6387b2ba56a
- Size of remote file:
- 2.48 kB
- SHA256:
- 7ec687911cb81e5994a95ebae35370b2054083e9e06bf60529648a5323d55401
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