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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3845489df76ed1c43c6b1481f39e76c9dd5a8757251f520a50181edc619da17
- Size of remote file:
- 1.42 GB
- SHA256:
- 8576ce97fdbc776150b9c4293fa2ffa0e2f1a2ce621b67ae8ec85a55224239a5
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