Zero-Shot Classification
Transformers
Safetensors
English
modernbert
text-classification
instruct
natural-language-inference
nli
mnli
Instructions to use tasksource/ModernBERT-base-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tasksource/ModernBERT-base-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="tasksource/ModernBERT-base-nli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tasksource/ModernBERT-base-nli") model = AutoModelForSequenceClassification.from_pretrained("tasksource/ModernBERT-base-nli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from tasksource/ModernBERT-base-nli: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/tasksource/ModernBERT-base-nli/resolve/main/model.safetensors
- Command line
-
hf download hf://tasksource/ModernBERT-base-nli/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/tasksource/ModernBERT-base-nli/resolve/main/model.safetensors
598 MB
- Xet hash:
- 04ad0c084e9c42833963ff5c69823128312f4abeea5246f5d98cbf890bce5f3e
- Size of remote file:
- 598 MB
- SHA256:
- 86c32c52ce38b8f26e028ca959b06daee3a5f3f6947c63258bc8695dde88a465
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