Instructions to use intelcomp/nace2_level1_20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_20 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_20")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_20") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db8ab6738595e2520c988d5494c6aa7ba88d187c20d416dd2aae568b56df94b3
- Size of remote file:
- 2.48 kB
- SHA256:
- 6a56018a07e606c57059ae9a62500cffc443058ed11e208a066fb9dd9513b1b7
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