Model card: the engine is Janas-LLM
Browse files
README.md
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- mixture-of-experts
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# Qwen3-Coder-Next for Janas
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No speed published for this model yet.
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These are the model's weights converted to **JNS**, the format of [Janas](https://github.com/prabanta-dev/janas),
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## Get it
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Janas for Linux x86-64 (Ubuntu 22.04, Debian 12 and later), then the model:
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```sh
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curl -LO https://github.com/prabanta-dev/janas/releases/latest/download/janas-linux-x86_64.tar.gz
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./janas-chat qwen3-coder-next
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```
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`janas-get` downloads the files of this repository and checks them against the fingerprints below; `janas-chat` with no model shows the catalog and downloads the one you choose. Building Janas from its sources instead: [prabanta-dev/janas](https://github.com/prabanta-dev/janas).
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## Files
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## What was changed
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These files are a modified work of the original model, as the Apache License 2.0 requires to be stated. Nothing was retrained or pruned: each file is a GGUF file quantized by the people named above, rewritten by Janas's `gguf2jns` in the order Janas reads it, with the metadata carried over. Each (layer, expert) has a slot of its own, so that the experts a token needs can be read from disk on their own. The experts' down matrices were then cut by Janas's `jns_planes` into three planes of two bits each: a reordering of the same bits, which with all three planes gives back the quantized weights to the last bit.
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## Licence and attribution
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- Model: [Qwen/Qwen3-Coder-Next](https://huggingface.co/Qwen/Qwen3-Coder-Next), by Alibaba Cloud (the Qwen team).
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- Quantized GGUF: [Qwen/Qwen3-Coder-Next-GGUF](https://huggingface.co/Qwen/Qwen3-Coder-Next-GGUF), by its authors.
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- Converted to JNS by the Janas project ([prabanta-dev/janas](https://github.com/prabanta-dev/janas), GPL-3.0-or-later; the licence of the engine does not apply to these files).
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The original repository carries no LICENSE file; its card declares Apache 2.0. `LICENSE` here is the licence's text as the Apache Software Foundation publishes it.
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- mixture-of-experts
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---
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+
# Qwen3-Coder-Next for Janas-LLM
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No speed published for this model yet.
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These are the model's weights converted to **JNS**, the format of Janas-LLM, the inference engine in C of [Janas](https://github.com/prabanta-dev/janas), for ordinary computers, with or without a GPU. The files are read by Janas-LLM only.
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## Get it
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Janas-LLM for Linux x86-64 (Ubuntu 22.04, Debian 12 and later), then the model:
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```sh
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curl -LO https://github.com/prabanta-dev/janas/releases/latest/download/janas-linux-x86_64.tar.gz
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./janas-chat qwen3-coder-next
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```
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`janas-get` downloads the files of this repository and checks them against the fingerprints below; `janas-chat` with no model shows the catalog and downloads the one you choose. Building Janas-LLM from its sources instead: [prabanta-dev/janas](https://github.com/prabanta-dev/janas).
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## Files
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## What was changed
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+
These files are a modified work of the original model, as the Apache License 2.0 requires to be stated. Nothing was retrained or pruned: each file is a GGUF file quantized by the people named above, rewritten by Janas-LLM's `gguf2jns` in the order Janas reads it, with the metadata carried over. Each (layer, expert) has a slot of its own, so that the experts a token needs can be read from disk on their own. The experts' down matrices were then cut by Janas-LLM's `jns_planes` into three planes of two bits each: a reordering of the same bits, which with all three planes gives back the quantized weights to the last bit.
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## Licence and attribution
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- Model: [Qwen/Qwen3-Coder-Next](https://huggingface.co/Qwen/Qwen3-Coder-Next), by Alibaba Cloud (the Qwen team).
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- Quantized GGUF: [Qwen/Qwen3-Coder-Next-GGUF](https://huggingface.co/Qwen/Qwen3-Coder-Next-GGUF), by its authors.
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- Converted to JNS by the Janas project with Janas-LLM ([prabanta-dev/janas](https://github.com/prabanta-dev/janas), GPL-3.0-or-later; the licence of the engine does not apply to these files).
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The original repository carries no LICENSE file; its card declares Apache 2.0. `LICENSE` here is the licence's text as the Apache Software Foundation publishes it.
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