add qwen3-coder-next.knot (qwen3next fat-station knot)

.gitattributes

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+qwen3-coder-next.knot filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-Coder-Next
+tags:
+  - knot
+  - fat-station
+  - distributed-inference
+  - qwen3next
+  - moe
+---
+
+# qwen3-coder-next.knot
+
+Sovereign `.knot` encoding of **Qwen3-Coder-Next** (`arch=qwen3next`) for the
+Gnosis fat-station runtime. Converted from GGUF with `gguf-to-knot.py`
+(K-quant block passthrough, arch-aware config).
+
+## Why a knot
+
+`.knot` is a range-addressable weight container: a station fetches only the
+tensors for the layers it owns, over HTTP, instead of loading a whole file.
+That is what lets an A3B MoE this size run **sharded across Cloudflare
+Containers** (12 GiB each) rather than needing one large host.
+
+## Architecture
+
+Hybrid Mamba-2 gated-DeltaNet SSM with periodic full attention, and a
+sparse MoE FFN on every layer. Roughly 3B parameters are active per token.
+Long context is cheap because only the periodic attention layers carry a
+KV cache.
+
+## Serving
+
+Pipeline-parallel across N stations, each owning a contiguous layer range:
+
+```
+FAT_STATION_KNOT=<this knot url>
+FAT_STATION_SHARDED=1
+FAT_STATION_ROLE=entry|mid|exit
+FAT_STATION_LAYERS=0..6
+```
+
+MoE shards cleanly along layers: a layer owns its entire expert set, so
+top-k routing never needs a tensor held by another station.
+
+Published by AFFECTIVELY. https://huggingface.co/forkjoin-ai

qwen3-coder-next.knot

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