Zero-Shot Classification
Transformers
Safetensors
English
deberta-v2
text-classification
deberta
deberta-v3
stance-classification
nli
political-science
social-groups
parliamentary-debates
Instructions to use maxwlnd/socialgroup_stance_classification_nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maxwlnd/socialgroup_stance_classification_nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="maxwlnd/socialgroup_stance_classification_nli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("maxwlnd/socialgroup_stance_classification_nli") model = AutoModelForSequenceClassification.from_pretrained("maxwlnd/socialgroup_stance_classification_nli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from maxwlnd/socialgroup_stance_classification_nli: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/maxwlnd/socialgroup_stance_classification_nli/resolve/main/tokenizer.json
- Command line
-
hf download hf://maxwlnd/socialgroup_stance_classification_nli/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/maxwlnd/socialgroup_stance_classification_nli/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.