Instructions to use selsar/nli-social-groups with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selsar/nli-social-groups with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selsar/nli-social-groups")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selsar/nli-social-groups") model = AutoModelForSequenceClassification.from_pretrained("selsar/nli-social-groups", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from selsar/nli-social-groups: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/selsar/nli-social-groups/resolve/main/tokenizer.json
- Command line
-
hf download hf://selsar/nli-social-groups/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/selsar/nli-social-groups/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 4a67964e4d03f92df5ed0d961c7a18afae2a7e55a7cb7c56a7b63a50d5c98a26
- Size of remote file:
- 16.3 MB
- SHA256:
- dae67635485d9068cd054243182d2f964261eb001f8264de2f1d9c512c619015
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