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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3.5-2B
+tags: [webgpu, wgsl, gptq, int4, browser, text-generation, deltanet]
+---
+
+# qwen35-2b-webgpu — GPTQ-int4 weights
+
+Custom GPTQ-int4 quant (group 32, byte-sliced nibbles, single tied q4 copy of
+the 248k-vocab embedding serving both the gather and the logits cascade) of
+[Qwen/Qwen3.5-2B](https://huggingface.co/Qwen/Qwen3.5-2B) (text part), in the
+wire format of the
+[qwen35-2b-webgpu](https://huggingface.co/spaces/borkiss/qwen35-2b-webgpu-demo) browser runtime.
+
+**The first hybrid gated-DeltaNet + gated-attention LLM running in the
+browser** — pure WebGPU, hand-written WGSL kernels (chunked WY-representation
+delta-rule prefill, fused recurrent decode step, f32 state), no ONNX /
+transformers.js / GGUF.
+
+- ~1.07 GB; GPTQ calibrated on **chat-formatted** passages.
+- The runtime is verified against a PyTorch f32 reference (per-layer rms,
+  cascaded argmax bit-exact vs the exact-logits path).
+
+Try it: **https://huggingface.co/spaces/borkiss/qwen35-2b-webgpu-demo** · run /web/bench.html
+on your GPU and share the .log.

weights/manifest.q4.json

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