Instructions to use intelcomp/nace2_level1_27 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_27 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_27")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_27") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_27") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94336b58892ed2da4e57ce061cfe729ebd97a1d85accb417247f38c9c1546cb2
- Size of remote file:
- 2.48 kB
- SHA256:
- 80b5304c1d4dbdd52144fd14847530527f05716e9cb520d7b32b1e114f81642c
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