boboliu / text-classification updated 1 year ago

Qwen3-Reranker-4B-W4A16-G128

GPTQ Quantized Qwen/Qwen3-Reranker-4B with Ultrachat, THUIR/T2Ranking and m-a-p/COIG-CQIA for calibration set.

Params
4.1 B
Context
40,960
Downloads 30d
586 K
Likes
2
Commercial use: allowed apache-2.0 Not gated SAFETENSORS View on Hugging Face ↗

Download history

daily snapshots · 55 days
▲ 10 K in the last 30 days (1.7%)
587 K528 K
Jul 28Aug 15Sep 2Sep 20

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
model.safetensors i32 2.7 GB 4.0 GB ✅ Runs comfortably
model.safetensors (bf16, full) bf16 + 40K ctx 2.7 GB 6.5 GB ✅ Runs comfortably
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Architecture
Qwen3ForCausalLM
Parameters
4.1 B
Tensor type
I32
Context length
40,960
Vocabulary
151,669
Layers / heads
36 / 32
Licence
apache-2.0
First seen on the Hub
2025-06-07
Training datasets
undisclosed
Added to our catalog
2026-07-28
Compare with any text-classification model