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Gostar

gostar77

Models in Library1
Datasets in Library1
Models on Hugging Face1
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This profile connects the 2 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Text generation.

Reported licenses: other. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

A checkpoint-specific calibrated quantization of Qwen/Qwen3.8-Flash-Next for the Radiance inference engine. This repository contains a single self-contained.rad inference container. It is not a Transformers, safetensors, llama.cpp, or vLLM checkpoint. Use a Radiance build with the Qwen3.8-Flash-Next model support and w4nl/w5nl expert kernels. - All 48 calibrated trunk layers use GPTQ with three coordinate-descent sweeps. - Routed expert down projections use non-linear w5nl (5-bit) codebooks, group 64, E4M3 scales, and FWHT128. - Routed expert gate/up projections use w4nl (4-bit) with the same transform and group structure. - Ten selected high-energy routed experts remain BF16. - Attention…

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Datasets

Checkpoint-specific RADGRAM2 calibration statistics for converting the original BF16 Qwen/Qwen3.8-Flash-Next checkpoint with Radiance's GPTQ converter. These are calibration Grams, not a fine-tune, adapter, model checkpoint, or training dataset. They are intended for Radiance conversion recipes that use w4nl/w5nl expert quantization. - grams/part-00/, grams/part-01/, and grams/part-02/: all 24,768 RADGRAM2 files for both tensor-parallel ranks. The files are sharded because the Hub limits a single directory to 10,000 files. - reassemble-grams.sh: creates the flat grams-flat/ directory expected by Radiance. - grams-validation.json: structural and coverage validation results.…

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