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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee97c2d5a83a9d184b1fc99e75e0b0630165de1eb31fa23a78d6ccc856455ec0
- Size of remote file:
- 2.48 kB
- SHA256:
- 3e29be6c16f421407d80ba77f94e95f9e2710e715b9e56f70d2f57544f489847
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