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mmbert32k-factcheck-classifier-merged
vllm-sr/mmbert32k-factcheck-classifier-merged
mmbert32k-factcheck-classifier-merged is a text classification model from vllm-sr. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
This is the merged version of the mmBERT-32K factcheck classifier model, ready for direct inference without PEFT.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- modernbert
- Access
- Public
- Created
- Jan 31, 2026
- Updated
- Oct 2, 2026
- SHA
- 88b7e3c3
Base models
Model card
From the Hugging Face model README
mmBERT-32K Factcheck Classifier (Merged)
This is the merged version of the mmBERT-32K factcheck classifier model, ready for direct inference without PEFT.
Model Details
- Base Model: vllm-sr/mmbert-32k-yarn
- Task: Text Classification
- Number of Labels: 2
- Context Length: 32,768 tokens
- Architecture: ModernBERT with YaRN RoPE scaling
Usage
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained(
"vllm-sr/mmbert32k-factcheck-classifier-merged",
trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained("vllm-sr/mmbert32k-factcheck-classifier-merged")
# Inference
inputs = tokenizer("Your text here", return_tensors="pt", truncation=True, max_length=32768)
outputs = model(**inputs)
Related Models
- LoRA Adapter: vllm-sr/mmbert32k-factcheck-classifier-lora
- Base Model: vllm-sr/mmbert-32k-yarn
License
Apache 2.0
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Languages
- multilingual
- Created
- Jan 31, 2026
- Updated
- Oct 2, 2026