Text Classification
PEFT
Safetensors
Transformers
English
reddit
conversation-analysis
constructive-dialogue
modernbert
lora
lightweight
high-throughput
Instructions to use NiklasKoch/modernbert-discussion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NiklasKoch/modernbert-discussion-classifier with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("answerdotai/ModernBERT-base") model = PeftModel.from_pretrained(base_model, "NiklasKoch/modernbert-discussion-classifier") - Transformers
How to use NiklasKoch/modernbert-discussion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NiklasKoch/modernbert-discussion-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NiklasKoch/modernbert-discussion-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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datasets:
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- reddit
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pipeline_tag: text-classification
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---
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# ModernBERT Reddit Discussion Classifier
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- **Task**: Binary classification of conversation constructiveness
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- **Language**: English
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## Intended Uses
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### Primary Use Case
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datasets:
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- reddit
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pipeline_tag: text-classification
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repo_url: https://github.com/Niklas257/Reddit-Constructiveness-Classification.git
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---
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# ModernBERT Reddit Discussion Classifier
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- **Task**: Binary classification of conversation constructiveness
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- **Language**: English
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### Model Source
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- **Repository**: https://github.com/Niklas257/Reddit-Constructiveness-Classification.git
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## Intended Uses
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### Primary Use Case
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