perplexity-ai/pplx-decider-v1.1-27b

text-classification model by perplexity-ai

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pplx-decider-v1.1-27b is an update of our pplx-decider-v1-27b model, that boost the Decision Index score from 56.4 to 61.56, now outperforming Jev by more than 3.5 points, while using the same backbone. Most of the gains are driven by the lifting of the causal mask and training on more data, including data from tasksource. The overall score uses the suite's weighting, not a simple category average. This is the native decision-checkpoint layout: a Qwen35Model backbone plus readout.safetensors containing a BF16 [255, 5120] decision head. The Transformers class name does not change the base model identity, Qwen3.8-27B. Use the included inference implementation to preserve the evaluated behavior: linear-attention layers retain their native behavior. Default causal inference does not reproduce this checkpoint's evaluated setup. When using logits directly, apply it exactly once and normalize over the valid candidates for the current decision. A serving system requiring Qwen35ForConditionalGeneration needs a separate export, mapping readout…

perplexity-ai/pplx-decider-v1.1-27b on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. pplx-decider-v1.1-27b
  2. Evaluation
  3. Checkpoint format and serving
  4. Usage
  5. Images
  6. Acknowledgment

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Model overview

perplexity-ai/pplx-decider-v1.1-27b is a text-classification model repository published by perplexity-ai on Hugging Face. The source reports the pytorch library.

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Model facts

Task
text-classification
Library
pytorch
Recent downloads (30 days)
3,819
Cumulative likes
154
Hugging Face trending score
59
Reported safetensors parameters
26,085,330,160
Architecture
Qwen3_5Model
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-10-05T12:32:27.000Z
Last modified
2026-10-12T07:26:21.000Z

Compatibility and lineage

Language coverage was not reported.

Reported base models: Qwen/Qwen3.8-27B

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-10-17T06:41:56.108Z. Daily imports are snapshots, not real-time monitoring.

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