Add GGUF quantizations

.gitattributes

@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+aria-gemma4-31b-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+aria-gemma4-31b-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+aria-gemma4-31b-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+aria-gemma4-31b-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+aria-gemma4-31b.imatrix filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+license: gemma
+base_model: xlr8harder/aria-gemma4-31b-identity-epoch2-temp-20260414_094544_epoch2_best
+base_model_relation: quantized
+library_name: gguf
+tags:
+- gguf
+- llama.cpp
+- lmstudio
+- quantized
+- gemma4
+- text-generation
+---
+
+# Aria Gemma 4 31B Identity Epoch 2 GGUF
+
+GGUF quantizations of `xlr8harder/aria-gemma4-31b-identity-epoch2-temp-20260414_094544_epoch2_best` for llama.cpp and LM Studio.
+
+## Recommended Files
+
+| File | Size | Sampled train PPL | Notes |
+|---|---:|---:|---|
+| `aria-gemma4-31b-Q4_K_M.gguf` | 18G | 2.5489 | Recommended default. |
+| `aria-gemma4-31b-Q4_K_S.gguf` | 17G | 2.5524 | Smaller 4-bit fallback. |
+| `aria-gemma4-31b-Q5_K_M.gguf` | 21G | 2.5117 | Higher quality option. |
+| `aria-gemma4-31b-Q8_0.gguf` | 31G | 2.5023 | Reference quant. |
+
+F16 GGUF baseline on the same sampled text: PPL `2.4993`.
+
+## Calibration And Evaluation
+
+The K-quants were built with llama.cpp `llama-imatrix` using 256 sampled calibration examples:
+
+- 192 identity training examples
+- 64 WildChat anchor training examples
+
+Perplexity was evaluated on 200 sampled training examples:
+
+- 100 identity training examples
+- 100 WildChat anchor training examples
+
+The `.imatrix` file is the llama.cpp importance-matrix calibration artifact used during quantization. It is not required for inference, but it is included for reproducibility and future re-quantization.
+
+## llama.cpp Example
+
+```bash
+PROMPT=$'<bos><|turn>user\nWhat is your name?<turn|>\n<|turn>model\n<think>\n'
+
+llama-cli \
+  -m aria-gemma4-31b-Q4_K_M.gguf \
+  -p "$PROMPT" \
+  -c 4096 \
+  -ngl 999 \
+  -n 256 \
+  --reverse-prompt '<turn|>' \
+  --no-display-prompt \
+  -st \
+  --simple-io \
+  --temp 0.7 \
+  --top-p 0.95
+```
+
+This checkpoint was trained with literal `<think>...</think>` traces in the assistant text. The prompt above pre-fills `<think>` to match that training format.
+
+## Build Notes
+
+- Quantized with llama.cpp commit `1f30ac0`.
+- The source model's context length is preserved in GGUF metadata as `262144`.
+- `Q4_K_M` was smoke-tested with llama.cpp on an A100 and generated a valid identity response with a `<think>...</think>` trace.

aria-gemma4-31b-Q4_K_M.gguf

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eval/ppl-aria-gemma4-31b-F16.log

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+

eval/text_metadata.json

@@ -0,0 +1,11 @@
+{
+  "model_dir": "/alloc/gemma4_full_sft_recipe/runs/aria_gemma4_31b_identity_rerun_lr2e6_ep5_ga4_anchor10_20260414_094544/merged_epoch2_best",
+  "seed": 42,
+  "calibration_samples": 256,
+  "eval_samples": 200,
+  "calibration_identity_samples": 192,
+  "calibration_anchor_samples": 64,
+  "eval_identity_samples": 100,
+  "eval_wildchat_samples": 100,
+  "eval_from_train": true
+}