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")# 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
- Xet hash:
- 864ba6b53560f37c6506faef419ae3075df7bedf69677c4aa257ca1700b5ef44
- Size of remote file:
- 738 MB
- SHA256:
- 6d0fd395b48812d53347c6edfbc3d5c9489c20f3d925ed8392a7b127ba2fda68
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