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
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README.md
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language:
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pipeline_tag: zero-shot-classification
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---
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# Model Card for Model ID
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Work in progress
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ModernBERT fine-tuned on tasksource NLI tasks (>20 nli datasets, including MNLI, ANLI, SICK, WANLI, doc-nli, LingNLI, FOLIO, FOL-NLI, LogicNLI, Label-NLI...)
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```
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@inproceedings{sileo-2024-tasksource,
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title = "tasksource: A Large Collection of {NLP} tasks with a Structured Dataset Preprocessing Framework",
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language:
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- en
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pipeline_tag: zero-shot-classification
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datasets:
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- nyu-mll/glue
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- facebook/anli
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---
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# Model Card for Model ID
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ModernBERT fine-tuned on tasksource NLI tasks (>20 nli datasets, including MNLI, ANLI, SICK, WANLI, doc-nli, LingNLI, FOLIO, FOL-NLI, LogicNLI, Label-NLI...)
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Work in progress.
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```
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@inproceedings{sileo-2024-tasksource,
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title = "tasksource: A Large Collection of {NLP} tasks with a Structured Dataset Preprocessing Framework",
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