Instructions to use intelcomp/nace2_level1_25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_25 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_25")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_25") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_25") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5ae151b155768278afdcae601772ce2d114f0b662999cd7fbe16f46373d2752
- Size of remote file:
- 2.48 kB
- SHA256:
- 0c96fce6c03c7036bda8d6d9f590b0f619ce6226897e80f1ed70d2676b3862d3
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