Instructions to use intelcomp/nace2_level0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level0") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b679a8b60270be450597495c9211647414d7ccb0ceab75fc219eb480e57a8497
- Size of remote file:
- 15.5 kB
- SHA256:
- 02799ae29d8e97c746469176f763b32351e4563ab92507ce57bd575981b0b31a
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