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DeepDavid/gemma-4-31b-it-qcache-q4k
gemma-4-31b-it-qcache-q4k is a machine learning model from DeepDavid. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as gemma.
Quantized deployment artifacts for google/gemma-4-31b-it.
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.gguf17.3 GB · 72%
From the Hugging Face model README
Quantized deployment artifacts for google/gemma-4-31b-it.
qcache-q4_k.v1.gguf — GGML Q4_K tensors for the model's linear projections,
stored in a GGUF container keyed by the original checkpoint tensor paths
(no metadata KVs). Produced by in-memory quantization of the bf16
checkpoint with a candle-based
loader.aux-tensors.safetensors — everything the cache does not carry:
embeddings, norms, and the full-attention layers' projections kept in
bf16. Keeping the global-attention projections unquantized matters:
4-bit error concentrated in those layers collapses long-range retrieval
(needle recall degrades beyond ~2x the sliding window with them
quantized, and is exact with them in bf16).Format note: this is not a llama.cpp-compatible GGUF — tensors keep their original checkpoint names and only linear projections are quantized. Load it with a runtime that pairs the cache with the auxiliary safetensors.
Weights are redistributed under the same terms as the base model.