Instructions to use intelcomp/nace2_level1_25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_25 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_25")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_25") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_25") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 982fe291ad266b2dcf825e31ae55b071f490c4f3e689bd0f6fbacc7e206d2cfe
- Size of remote file:
- 1.42 GB
- SHA256:
- 7ba741b44af928ff4d276d7b771ccf6021c9f91d856e4771436503eb1a50fe08
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