Instructions to use intelcomp/nace2_level1_28 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/nace2_level1_28 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/nace2_level1_28")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/nace2_level1_28") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/nace2_level1_28", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from intelcomp/nace2_level1_28: direct link, hf CLI and curl.
- Browser
- Download file 15.5 kB
-
https://huggingface.co/intelcomp/nace2_level1_28/resolve/main/rng_state.pth
- Command line
-
hf download hf://intelcomp/nace2_level1_28/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/intelcomp/nace2_level1_28/resolve/main/rng_state.pth
15.5 kB
- Xet hash:
- 2befffdc19f9f67c48e497339f817b08c5a57ce69a8f188cd03bb3c002de7bf0
- Size of remote file:
- 15.5 kB
- SHA256:
- 9a9d0add05500e427d7ed5e950ba488ee4ff92ba1bb784bc84bd405999491ff2
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