---
language:
- en
pipeline_tag: text-classification
tags:
- political-nlp
- political-ideology
- viewpoint-classification
- political-slant
- us-politics
- stance-detection
- binary-classification
- ensemble
- mixture-model
- probability-calibration
- mistral
- qwen
- lora
- mlx
- apple-silicon
- english-text-classification
base_model:
- mlx-community/Mistral-7B-v0.3-4bit
- mlx-community/Qwen3.5-9B-4bit
---
# PoSSUM
![PoSSUM model card](cover.png)

David Driscoll · Political Slant Scoring Using Mixtures. Classifies the viewpoint expressed in short English passages about U.S. politics as left or right.

**Frozen MITweet topic test (159 passages)** · Macro-F1 **0.890** · balanced accuracy **0.872** · log loss **0.241**.

Download with `hf download ddrisco11/PoSSUM --local-dir PoSSUM`. The bundle contains the Mistral LoRA, both calibrators and mixture weights. MLX inference requires the separately downloaded base models listed above.

[GitHub and inference code](https://github.com/ddrisco11/PoSSUM) · [Evaluation report and pinned base revisions](https://github.com/ddrisco11/PoSSUM/blob/main/reports/human-model-release.json)

**Sources** · [MITweet dataset and citation](https://github.com/LST1836/MITweet) · [Synthetic development data](https://huggingface.co/datasets/JyotiNayak/political_ideologies) · [Mistral 7B v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) · [Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) · [Hu et al., LoRA](https://arxiv.org/abs/2106.09685).