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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ad42bd4956d283daf37898841055229d816f1ee6a8c92470744997b3f5548b0
- Size of remote file:
- 1.42 GB
- SHA256:
- c78c0caf266fceb54410a6890dc8a9ab1e5698014bc502410aee8255ce8b5549
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