Instructions to use intelcomp/nace2_level1_26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_26 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_26")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_26") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_26", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b9f2d659334d101966369362c4ecbc0a607ea186f6efb3b147573cad98affec
- Size of remote file:
- 2.48 kB
- SHA256:
- b6aa0846dd9ca1e77ecbd0d74050468ddc827f500dcb70b87bbc559b37d1e7ca
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