Update Hermes-tuned KXL naming and visuals

README.md

@@ -60,7 +60,7 @@ The accepted fused MLX checkpoint passed the parser-disabled fixed-Hermes suite
 
 ![GGUF quant size and quality](visuals/gguf_quant_size_quality.svg)
 
-The GGUF path exports from a dequantized BF16/HF source, then produces stock llama.cpp XL-approximation quants using tensor-type policies and the Hermes/tool-router imatrix. All four released quants passed the same 43-case fixed-Hermes eval at 64K context.
+The GGUF path exports from a dequantized BF16/HF source, then produces Hermes-tuned KXL quants using stock llama.cpp tensor-type policies and the Hermes/tool-router imatrix. All four released quants passed the same 43-case fixed-Hermes eval at 64K context.
 
 ## What Was Trained
 
@@ -167,14 +167,14 @@ if "conv.conv" in name:
 
 Without that patch, `conv.conv.weight` stayed 3D and llama.cpp failed while loading the BF16 GGUF parent. With the patch, the BF16 parent loaded and generated normally.
 
-Four Unsloth-style XL approximation quants were generated from the BF16 parent using stock llama.cpp `--tensor-type-file` overrides plus a Hermes/tool-router imatrix. These are not byte-identical Unsloth Dynamic 2.0 quants; they are behavior- and size-targeted approximations.
+Four Hermes-tuned KXL quants were generated from the BF16 parent using stock llama.cpp `--tensor-type-file` overrides plus a Hermes/tool-router imatrix. They target Unsloth-style XL size/behavior buckets, but are not a claim of byte-identical Unsloth Dynamic 2.0 generation.
 
 | GGUF artifact | Size | llama.cpp 64K fixed-Hermes eval |
 |---|---:|---:|
-| `Q8_K_XL_APPROX` | 8.6G | 43/43 |
-| `Q6_K_XL_APPROX` | 7.1G | 43/43 |
-| `Q5_K_XL_APPROX` | 6.5G | 43/43 |
-| `Q4_K_XL_APPROX` | 5.7G | 43/43 |
+| `LFM-2.5-8B-1B-Hermes-Tuned-Q8KXL.gguf` | 8.6G | 43/43 |
+| `LFM-2.5-8B-1B-Hermes-Tuned-Q6KXL.gguf` | 7.1G | 43/43 |
+| `LFM-2.5-8B-1B-Hermes-Tuned-Q5KXL.gguf` | 6.5G | 43/43 |
+| `LFM-2.5-8B-1B-Hermes-Tuned-Q4KXL.gguf` | 5.7G | 43/43 |
 
 Each llama.cpp eval returned structured OpenAI-compatible `message.tool_calls` with `finish_reason: "tool_calls"` for all 28 tool-call cases, and produced no false-positive tool calls on the 10 no-tool cases.
 

evals/gguf_Q4KXL_llamacpp_all_fixed_hermes.json

@@ -0,0 +1,1358 @@
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evals/gguf_Q5KXL_llamacpp_all_fixed_hermes.json

@@ -0,0 +1,1358 @@
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evals/gguf_Q6KXL_llamacpp_all_fixed_hermes.json

@@ -0,0 +1,1358 @@
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evals/gguf_Q8KXL_llamacpp_all_fixed_hermes.json

@@ -0,0 +1,1358 @@
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+      "finish_reason": "stop",
+      "content": "A browser is an application for navigating and interacting with web pages, while a terminal is an application for running shell commands.",
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+      "finish_reason": "stop",
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+      "finish_reason": "stop",
+      "content": "marker: holdout-fixed",
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+      "category": "finalization",
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+      "failure": null,
+      "elapsed_s": 0.288,
+      "finish_reason": "stop",
+      "content": "fixed-hermes",
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+}

gguf/Q4KXL.tensor-types.txt

@@ -0,0 +1,10 @@
+token_embd=q6_k
+output=q6_k
+attn_q=q6_k
+attn_k=q6_k
+attn_v=q5_k
+attn_output=q5_k
+gate=q8_0
+router=q8_0
+norm=f16
+ffn=q4_k

gguf/Q5KXL.tensor-types.txt

@@ -0,0 +1,7 @@
+token_embd=q8_0
+output=q8_0
+attn=q6_k
+gate=q8_0
+router=q8_0
+norm=f16
+ffn=q5_k

gguf/Q6KXL.tensor-types.txt

@@ -0,0 +1,10 @@
+token_embd=q8_0
+output=q8_0
+attn_q=q8_0
+attn_k=q8_0
+attn_v=q8_0
+attn_output=q8_0
+gate=q8_0
+router=q8_0
+norm=f16
+ffn=q6_k

gguf/Q8KXL.tensor-types.txt

@@ -0,0 +1,7 @@
+token_embd=f16
+output=f16
+attn=q8_0
+gate=q8_0
+router=q8_0
+norm=f16
+ffn=q8_0

gguf/xl_quant_plan.json

@@ -1,22 +1,22 @@
 {
-  "note": "Approximate Unsloth Dynamic XL policies for stock llama.cpp. These are not byte-identical Unsloth Dynamic 2.0 quants.",
+  "note": "Hermes-tuned KXL policies for stock llama.cpp targeting Unsloth-style Dynamic XL buckets. These are not a claim of byte-identical Unsloth Dynamic 2.0 quants unless generated by Unsloth tooling.",
   "bf16_parent": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/bf16/LFM-2.5-8B-1B-hermes-ft-BF16.gguf",
   "imatrix": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/calibration/hermes_tool_router_imatrix.gguf",
   "commands": [
     {
-      "name": "UD-Q8_K_XL_APPROX",
+      "name": "Q8KXL",
       "base_quant": "Q8_0",
       "target_gb": 9.34,
-      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q8_K_XL_APPROX.tensor-types.txt",
-      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q8_K_XL_approx.gguf",
+      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q8KXL.tensor-types.txt",
+      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q8KXL.gguf",
       "command": [
         "llama-quantize",
         "--tensor-type-file",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q8_K_XL_APPROX.tensor-types.txt",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q8KXL.tensor-types.txt",
         "--imatrix",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/calibration/hermes_tool_router_imatrix.gguf",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/bf16/LFM-2.5-8B-1B-hermes-ft-BF16.gguf",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q8_K_XL_approx.gguf",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q8KXL.gguf",
         "Q8_0"
       ],
       "policy": {
@@ -62,19 +62,19 @@
       }
     },
     {
-      "name": "UD-Q6_K_XL_APPROX",
+      "name": "Q6KXL",
       "base_quant": "Q6_K",
       "target_gb": 7.74,
-      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q6_K_XL_APPROX.tensor-types.txt",
-      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q6_K_XL_approx.gguf",
+      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q6KXL.tensor-types.txt",
+      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q6KXL.gguf",
       "command": [
         "llama-quantize",
         "--tensor-type-file",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q6_K_XL_APPROX.tensor-types.txt",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q6KXL.tensor-types.txt",
         "--imatrix",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/calibration/hermes_tool_router_imatrix.gguf",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/bf16/LFM-2.5-8B-1B-hermes-ft-BF16.gguf",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q6_K_XL_approx.gguf",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q6KXL.gguf",
         "Q6_K"
       ],
       "policy": {
@@ -135,19 +135,19 @@
       }
     },
     {
-      "name": "UD-Q5_K_XL_APPROX",
+      "name": "Q5KXL",
       "base_quant": "Q5_K_M",
       "target_gb": 6.39,
-      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q5_K_XL_APPROX.tensor-types.txt",
-      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q5_K_XL_approx.gguf",
+      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q5KXL.tensor-types.txt",
+      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q5KXL.gguf",
       "command": [
         "llama-quantize",
         "--tensor-type-file",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q5_K_XL_APPROX.tensor-types.txt",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q5KXL.tensor-types.txt",
         "--imatrix",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/calibration/hermes_tool_router_imatrix.gguf",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/bf16/LFM-2.5-8B-1B-hermes-ft-BF16.gguf",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q5_K_XL_approx.gguf",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q5KXL.gguf",
         "Q5_K_M"
       ],
       "policy": {
@@ -193,19 +193,19 @@
       }
     },
     {
-      "name": "UD-Q4_K_XL_APPROX",
+      "name": "Q4KXL",
       "base_quant": "Q4_K_M",
       "target_gb": 5.35,
-      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q4_K_XL_APPROX.tensor-types.txt",
-      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q4_K_XL_approx.gguf",
+      "tensor_type_file": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q4KXL.tensor-types.txt",
+      "output": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q4KXL.gguf",
       "command": [
         "llama-quantize",
         "--tensor-type-file",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/UD-Q4_K_XL_APPROX.tensor-types.txt",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/Q4KXL.tensor-types.txt",
         "--imatrix",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/calibration/hermes_tool_router_imatrix.gguf",
         "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/bf16/LFM-2.5-8B-1B-hermes-ft-BF16.gguf",
-        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-hermes-ft-Q4_K_XL_approx.gguf",
+        "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/xl_quant_policies/LFM-2.5-8B-1B-Hermes-Tuned-Q4KXL.gguf",
         "Q4_K_M"
       ],
       "policy": {
@@ -266,4 +266,4 @@
       }
     }
   ]
-}
+}

release_summary.json

@@ -4,20 +4,20 @@
   "dequantized_hf_source": "release_work/model_upload_iter10_fused_dequantized",
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   "gguf_quants": {
-    "LFM-2.5-8B-1B-hermes-ft-Q4_K_XL_APPROX.gguf": {
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+    "LFM-2.5-8B-1B-Hermes-Tuned-Q4KXL.gguf": {
+      "path": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/quants/LFM-2.5-8B-1B-Hermes-Tuned-Q4KXL.gguf",
       "bytes": 6166588512
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-    "LFM-2.5-8B-1B-hermes-ft-Q5_K_XL_APPROX.gguf": {
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+    "LFM-2.5-8B-1B-Hermes-Tuned-Q5KXL.gguf": {
+      "path": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/quants/LFM-2.5-8B-1B-Hermes-Tuned-Q5KXL.gguf",
       "bytes": 6928018528
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-    "LFM-2.5-8B-1B-hermes-ft-Q6_K_XL_APPROX.gguf": {
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+    "LFM-2.5-8B-1B-Hermes-Tuned-Q6KXL.gguf": {
+      "path": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/quants/LFM-2.5-8B-1B-Hermes-Tuned-Q6KXL.gguf",
       "bytes": 7671360608
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-    "LFM-2.5-8B-1B-hermes-ft-Q8_K_XL_APPROX.gguf": {
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+    "LFM-2.5-8B-1B-Hermes-Tuned-Q8KXL.gguf": {
+      "path": "release_work/lfm25-moe8-mac-trainer/artifacts/gguf/quants/LFM-2.5-8B-1B-Hermes-Tuned-Q8KXL.gguf",
       "bytes": 9279548512
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@@ -34,7 +34,7 @@
       "content_text_tool_leaks": 0,
       "finish_reason_tool_calls": 28
     },
-    "gguf_q4_xl_approx_llamacpp_64k": {
+    "gguf_q4kxl_llamacpp_64k": {
       "passed": 43,
       "total": 43,
       "overall_rate": 1.0,
@@ -46,7 +46,7 @@
       "content_text_tool_leaks": 0,
       "finish_reason_tool_calls": 28
     },
-    "gguf_q5_xl_approx_llamacpp_64k": {
+    "gguf_q5kxl_llamacpp_64k": {
       "passed": 43,
       "total": 43,
       "overall_rate": 1.0,
@@ -58,7 +58,7 @@
       "content_text_tool_leaks": 0,
       "finish_reason_tool_calls": 28
     },
-    "gguf_q6_xl_approx_llamacpp_64k": {
+    "gguf_q6kxl_llamacpp_64k": {
       "passed": 43,
       "total": 43,
       "overall_rate": 1.0,
@@ -70,7 +70,7 @@
       "content_text_tool_leaks": 0,
       "finish_reason_tool_calls": 28
     },
-    "gguf_q8_xl_approx_llamacpp_64k": {
+    "gguf_q8kxl_llamacpp_64k": {
       "passed": 43,
       "total": 43,
       "overall_rate": 1.0,
@@ -86,7 +86,7 @@
   "llama_cpp_patch": "tools/llama-current/conversion/lfm2.py shortconv squeeze(-1) for LFM2/LFM2MoE conv.conv weights",
   "notes": [
     "Iter10 fixed-Hermes structured repair is the accepted adapter.",
-    "MLX fused and all llama.cpp XL approximation quants passed the 43-case parser-disabled fixed-Hermes suite.",
+    "MLX fused and all llama.cpp Hermes-tuned KXL quants passed the 43-case parser-disabled fixed-Hermes suite.",
     "GGUF XL quants are stock llama.cpp tensor-type-file/imatrix approximations, not byte-identical Unsloth Dynamic 2.0."
   ]
-}
+}

scripts/build_visual_assets.py

@@ -84,7 +84,7 @@ def render_pipeline() -> None:
         ("Repair adapters", "Iter01 to Iter10 LoRA", "structured tool-call targets", 994, 96, PURPLE),
         ("Parser-disabled evals", "MLX fixed-Hermes 43/43", "0 text-tool leaks", 274, 328, GREEN),
         ("Export path", "Fuse + dequantize", "HF/safetensors source for GGUF", 514, 328, BLUE),
-        ("XL GGUF quants", "Q4/Q5/Q6/Q8 approx", "all pass 43-case llama.cpp eval", 754, 328, TEAL),
+        ("XL GGUF quants", "Q4/Q5/Q6/Q8 KXL", "all pass 43-case llama.cpp eval", 754, 328, TEAL),
     ]
     body = header(
         "End-to-end local Mac fine-tuning pipeline",
@@ -241,21 +241,21 @@ def render_quant_size() -> None:
     rows = []
     for name, item in data["gguf_quants"].items():
         if "Q4" in name:
-            label = "Q4_K_XL"
+            label = "Q4KXL"
         elif "Q5" in name:
-            label = "Q5_K_XL"
+            label = "Q5KXL"
         elif "Q6" in name:
-            label = "Q6_K_XL"
+            label = "Q6KXL"
         else:
-            label = "Q8_K_XL"
+            label = "Q8KXL"
         rows.append((label, item["bytes"] / 1024**3))
     rows.sort(key=lambda x: x[1])
     width, height = 900, 460
     left, top, chart_w, chart_h = 90, 96, 680, 260
     max_size = max(v for _, v in rows) * 1.16
     body = header(
-        "GGUF XL approximation size/quality tradeoff",
-        "All four stock llama.cpp XL approximation quants passed the same 43-case fixed-Hermes suite at 64K context.",
+        "GGUF Hermes-tuned KXL size/quality tradeoff",
+        "All four stock llama.cpp KXL quants passed the same 43-case fixed-Hermes suite at 64K context.",
     )
     for i in range(5):
         y = top + chart_h - i * chart_h / 4