diff --git a/README.md b/README.md
index 5b2383a5895d837911e6aeb05227ed015f248060..d4fbe8ab7ff8833cf47fbe8f0a41a0dad01be98a 100644
--- a/README.md
+++ b/README.md
@@ -14,7 +14,7 @@ tags:
 - openvino
 pipeline_tag: text-classification
 base_model:
-- cross-encoder/mmarco-mMiniLMv2-L12-H384-v1
+- hotchpotch/mMiniLMv2-L12-H384
 ---
 
 # code-daemon-relation-v1
@@ -29,6 +29,11 @@ sweep a whole corpus — **~2 900 pairs/s** on a laptop RTX 5060 — and its hea
 marked entities directly instead of a whole-passage summary, so the relation is scored between
 them and in order. Multilingual: the XLM-R backbone reads prose and code comments in many languages.
 
+> The weights under this id were replaced on 2026-10-12. Same architecture, same inputs and
+> outputs, same tokenizer; the backbone is now the MIT-licensed
+> `hotchpotch/mMiniLMv2-L12-H384`, and macro-F1 on the held-out set moved from 0.57 to 0.60.
+> Engines built for the previous weights are gone from this repository.
+
 ## The four classes
 
 Wrap the entities in `[E1]…[/E1]` and `[E2]…[/E2]` in their own context.
@@ -54,7 +59,7 @@ training data is a zero-shot NLI model that scores each class as a hypothesis:
 
 | model | params | macro-F1 | "has a relation" F1 | P | R | pairs/s |
 |---|--:|--:|--:|--:|--:|--:|
-| **this model** | 117M | **0.569** | **0.810** | **0.793** | 0.828 | **351** |
+| **this model** | 117M | **0.598** | **0.798** | **0.786** | 0.811 | **351** |
 | mDeBERTa-v3-xnli, zero-shot | 279M | 0.194 | 0.699 | 0.538 | **0.997** | 61 |
 | always `NO_RELATION` | — | 0.158 | — | — | — | — |
 
@@ -63,9 +68,11 @@ training data is a zero-shot NLI model that scores each class as a hypothesis:
 - **5.8× faster on the same runtime, structurally**: zero-shot pays one forward pass per class,
   this pays one per pair. Speeds above are onnxruntime CUDA FP32 at batch 16 × seq 256; the
   shipped TensorRT engine is faster again.
-- **The trade:** three relation types plus abstain, nothing finer, and macro-F1 0.57 — the
-  classes are imbalanced and some boundaries are genuinely ambiguous. It is built for a
-  high-precision operating point: spot-check the edges at the `tau` you choose.
+- **The trade:** three relation types plus abstain, nothing finer, and macro-F1 0.60 — the
+  classes are imbalanced and some boundaries are genuinely ambiguous (per class on the same set:
+  `NO_RELATION` 0.76, `semantically_similar_to` 0.64, `supersedes_or_conflicts` 0.47,
+  `depends_on` 0.52). It is built for a high-precision operating point: spot-check the edges at
+  the `tau` you choose.
 
 ### Speed by lane
 
@@ -122,13 +129,15 @@ already have); entities more than a 256-token window apart.
 
 ## How it was made
 
-- **Warm start:** the multilingual ranking cross-encoder `mmarco-mMiniLMv2-L12-H384-v1`
-  (XLM-RoBERTa, 12 layers × 384), with four marker tokens added to its vocabulary.
-- **New head:** its single ranking logit was replaced by a 4-class layer over the hidden states at
-  the `[E1]` and `[E2]` positions, concatenated — not over `[CLS]`. Direction comes free: swap
-  the markers and the input genuinely changes.
+- **Backbone:** `hotchpotch/mMiniLMv2-L12-H384` — Microsoft's multilingual MiniLM v2 (12 layers ×
+  384, distilled from XLM-RoBERTa Large), a plain masked-language-model encoder with no
+  task-specific stage in front of it — with four marker tokens added to its vocabulary.
+- **Head:** a 4-class layer over the hidden states at the `[E1]` and `[E2]` positions,
+  concatenated — not over `[CLS]`. Direction comes free: swap the markers and the input genuinely
+  changes.
 - **Training:** sequence-level distillation from an LLM teacher on relation tuples, each grounded
-  in its passage; `NO_RELATION` is a trained class, not an inferred one.
+  in its passage, with a class-balanced (focal) objective; `NO_RELATION` is a trained class, not
+  an inferred one.
 - **FP16 engines**, not INT8: this architecture's activation outliers make INT8 calibration lossy.
 
 ## Files
@@ -138,24 +147,21 @@ already have); entities more than a 256-token window apart.
 | `model.onnx` + `model.onnx.data` | FP32 ONNX — the build source and the standalone path |
 | `model.safetensors`, `config.json` | the same weights: encoder as `roberta.*`, head as `classifier.weight` `[4, 768]` + `classifier.bias` (see below); the Apple (MLX) build is prepared from this pair |
 | `tokenizer.json`, `tokenizer_config.json`, `sentencepiece.bpe.model` | XLM-R tokenizer with the four marker tokens |
-| `code-daemon-relation-v1-{s,m,l}_{win_x64,linux_x64}_trt11.0_sm_{75,80,86,89,120}.engine` | TensorRT FP16 per bucket × OS × GPU; `sm_90` (H100/H200) Linux only |
+| `code-daemon-relation-v1-{s,m,l}_{win_x64,linux_x64}_trt11.3_sm_{75,80,86,89,90,120}.engine` | TensorRT FP16 per bucket × OS × GPU; `sm_90` (H100/H200) Linux only. The set is filled per architecture as each is built — the file list is the truth |
 | `code-daemon-relation-v1-{s,m,l}_ov2026.4_{cpu,igpu}_fp16_b16_s{64,128,256}.{xml,bin}` | OpenVINO 2026.4 FP16, Intel CPU / iGPU |
 | `coreml_ane/embed.mlpackage/` | Core ML for the Apple Neural Engine, functions `b16 s64 / s128 / s256`; load with `cpuAndNeuralEngine` |
 
 ⚠ The head is not the stock `transformers` one — `AutoModelForSequenceClassification` would
 initialise its own and ignore this. Load the encoder with `AutoModel`, mean-pool the last hidden
 state over the tokens equal to each marker id (`config.json` → `ultracode.entity_marker_ids`),
-concatenate the two and apply the classifier; that matches the ONNX to 2e-6.
+concatenate the two and apply the classifier; that matches the ONNX to 3e-6.
 
 ## License & attribution
 
 Released under the **MIT license**.
 
-⚠️ The warm-start base `cross-encoder/mmarco-mMiniLMv2-L12-H384-v1` derives from mMARCO ← MS MARCO,
-whose terms are **non-commercial research**. Whether a fine-tuned model inherits dataset-use terms
-is legally unsettled — this is **not legal advice**. Retrain from a permissive base if strict
-compliance matters to you.
-
-Warm-started from **[cross-encoder/mmarco-mMiniLMv2-L12-H384-v1](https://huggingface.co/cross-encoder/mmarco-mMiniLMv2-L12-H384-v1)**.
-Backbone: XLM-RoBERTa. Used by the [Code-Daemon](https://code-daemon.dev) code assistant,
-though nothing about the model is specific to it.
+Backbone: **[hotchpotch/mMiniLMv2-L12-H384](https://huggingface.co/hotchpotch/mMiniLMv2-L12-H384)**
+(MIT), Microsoft's
+[Multilingual-MiniLM-L12-H384](https://github.com/microsoft/unilm/tree/master/minilm) distilled
+from XLM-RoBERTa Large. Used by the [Code-Daemon](https://code-daemon.dev) code assistant, though
+nothing about the model is specific to it.
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deleted file mode 100644
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--- a/code-daemon-relation-v1-l_ov2026.4_cpu_fp16_b16_s256.xml
+++ /dev/null
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-<?xml version="1.0"?>
-<net name="onnx_Frontend_IR" version="11">
-	<layers>
-		<layer id="0" name="input_ids" type="Parameter" version="opset1">
-			<data shape="16,256" element_type="i64" />
-			<output>
-				<port id="0" precision="I64" names="input_ids">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="1" name="attention_mask" type="Parameter" version="opset1">
-			<data shape="16,256" element_type="i64" />
-			<output>
-				<port id="0" precision="I64" names="attention_mask">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="2" name="val_815" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="0" size="8" />
-			<output>
-				<port id="0" precision="I64" names="val_815" />
-			</output>
-		</layer>
-		<layer id="3" name="node_eq_614" type="Equal" version="opset1">
-			<data auto_broadcast="numpy" />
-			<input>
-				<port id="0" precision="I64">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-				<port id="1" precision="I64" />
-			</input>
-			<output>
-				<port id="2" precision="BOOL" names="eq_614">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="4" name="node__to_copy_3" type="Convert" version="opset1">
-			<data destination_type="f32" />
-			<input>
-				<port id="0" precision="BOOL">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-			</input>
-			<output>
-				<port id="1" precision="FP32" names="_to_copy_3">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="5" name="val_25" type="Const" version="opset1">
-			<data element_type="i64" shape="1" offset="8" size="8" />
-			<rt_info>
-				<attribute name="DisablePrecisionConversion" version="0" value="dynamic:f16" />
-			</rt_info>
-			<output>
-				<port id="0" precision="I64" names="val_25">
-					<dim>1</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="6" name="node_unsqueeze_2" type="Unsqueeze" version="opset1">
-			<input>
-				<port id="0" precision="FP32">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-				<port id="1" precision="I64">
-					<dim>1</dim>
-				</port>
-			</input>
-			<output>
-				<port id="2" precision="FP32" names="unsqueeze_2">
-					<dim>16</dim>
-					<dim>256</dim>
-					<dim>1</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="7" name="roberta.embeddings.word_embeddings.weight_compressed" type="Const" version="opset1">
-			<data element_type="f16" shape="250006, 384" offset="16" size="192004608" />
-			<output>
-				<port id="0" precision="FP16" names="roberta.embeddings.word_embeddings.weight">
-					<dim>250006</dim>
-					<dim>384</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="8" name="roberta.embeddings.word_embeddings.weight" type="Convert" version="opset1">
-			<data destination_type="f32" />
-			<rt_info>
-				<attribute name="decompression" version="0" />
-			</rt_info>
-			<input>
-				<port id="0" precision="FP16">
-					<dim>250006</dim>
-					<dim>384</dim>
-				</port>
-			</input>
-			<output>
-				<port id="1" precision="FP32">
-					<dim>250006</dim>
-					<dim>384</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="9" name="Constant_33" type="Const" version="opset1">
-			<data element_type="i64" shape="" offset="192004624" size="8" />
-			<output>
-				<port id="0" precision="I64" />
-			</output>
-		</layer>
-		<layer id="10" name="node_embedding" type="Gather" version="opset8">
-			<data batch_dims="0" />
-			<input>
-				<port id="0" precision="FP32">
-					<dim>250006</dim>
-					<dim>384</dim>
-				</port>
-				<port id="1" precision="I64">
-					<dim>16</dim>
-					<dim>256</dim>
-				</port>
-				<port id="2" precision="I64" />
-			</input>
-			<output>
-				<port id="3" precision="FP32" names="embedding">
-					<dim>16</dim>
-					<dim>256</dim>
-					<dim>384</dim>
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-			</output>
-		</layer>
-		<layer id="11" name="roberta.embeddings.token_type_embeddings.weight_compressed" type="Const" version="opset1">
-			<data element_type="f16" shape="1, 384" offset="192004632" size="768" />
-			<output>
-				<port id="0" precision="FP16" names="roberta.embeddings.token_type_embeddings.weight">
-					<dim>1</dim>
-					<dim>384</dim>
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-			</output>
-		</layer>
-		<layer id="12" name="roberta.embeddings.token_type_embeddings.weight" type="Convert" version="opset1">
-			<data destination_type="f32" />
-			<rt_info>
-				<attribute name="decompression" version="0" />
-			</rt_info>
-			<input>
-				<port id="0" precision="FP16">
-					<dim>1</dim>
-					<dim>384</dim>
-				</port>
-			</input>
-			<output>
-				<port id="1" precision="FP32">
-					<dim>1</dim>
-					<dim>384</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="13" name="roberta.embeddings.token_type_ids" type="Const" version="opset1">
-			<data element_type="i64" shape="1, 514" offset="192005400" size="4112" />
-			<output>
-				<port id="0" precision="I64" names="roberta.embeddings.token_type_ids">
-					<dim>1</dim>
-					<dim>514</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="14" name="ShapeOf_3" type="ShapeOf" version="opset3">
-			<data output_type="i64" />
-			<input>
-				<port id="0" precision="I64">
-					<dim>16</dim>
-					<dim>256</dim>
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-			<output>
-				<port id="1" precision="I64">
-					<dim>2</dim>
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-		</layer>
-		<layer id="15" name="Constant_4" type="Const" version="opset1">
-			<data element_type="i64" shape="1" offset="192004624" size="8" />
-			<rt_info>
-				<attribute name="DisablePrecisionConversion" version="0" value="dynamic:f16" />
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-		<layer id="16" name="Constant_5" type="Const" version="opset1">
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-				<port id="0" precision="I64">
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-		<layer id="17" name="Constant_6" type="Const" version="opset1">
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-				<attribute name="DisablePrecisionConversion" version="0" value="dynamic:f16" />
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-		<layer id="19" name="node_Shape_0" type="Slice" version="opset8">
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-			<output>
-				<port id="5" precision="I64" names="val_0">
-					<dim>1</dim>
-				</port>
-			</output>
-		</layer>
-		<layer id="20" name="val_7" type="Const" version="opset1">
-			<data element_type="i64" shape="1" offset="192009512" size="8" />
-			<rt_info>
-				<attribute name="DisablePrecisionConversion" version="0" value="dynamic:f16" />
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-		<layer id="21" name="node_Concat_8" type="Concat" version="opset1">
-			<data axis="0" />
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-		<layer id="22" name="node_expand" type="Broadcast" version="opset3">
-			<data mode="bidirectional" />
-			<input>
-				<port id="0" precision="I64">
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diff --git a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_120.engine b/code-daemon-relation-v1-s_win_x64_trt11.3_sm_120.engine
deleted file mode 100644
index 55cf4eb4931797a28a1c699673e2c51b95fd74da..0000000000000000000000000000000000000000
--- a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_120.engine
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6a18709f8ae6e6c97c5f1fb4b88a3eac1699a2c9443b81e24ef3de5ed06f8c51
-size 238321548
diff --git a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_75.engine b/code-daemon-relation-v1-s_win_x64_trt11.3_sm_75.engine
deleted file mode 100644
index 913376aa5831e54dbd111345211b41c3da2f4faa..0000000000000000000000000000000000000000
--- a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_75.engine
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:43c0ef8d8c46ee944422615f2a1e0ef20db4324077db6c3723427edee34bee67
-size 237063204
diff --git a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_80.engine b/code-daemon-relation-v1-s_win_x64_trt11.3_sm_80.engine
deleted file mode 100644
index 43b064c25fa053ebe324a0302855d17838ab93ea..0000000000000000000000000000000000000000
--- a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_80.engine
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:24c4762fa4dcc34da56822641abc248c739b0fb5f96b279a9293fc3c83c6f270
-size 238613724
diff --git a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_86.engine b/code-daemon-relation-v1-s_win_x64_trt11.3_sm_86.engine
deleted file mode 100644
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--- a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_86.engine
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
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-size 238579844
diff --git a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_89.engine b/code-daemon-relation-v1-s_win_x64_trt11.3_sm_89.engine
deleted file mode 100644
index 5555104b7ba1f3eebb12383957d98d17fa6fa568..0000000000000000000000000000000000000000
--- a/code-daemon-relation-v1-s_win_x64_trt11.3_sm_89.engine
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5bcb70ebda846a552e4f835666bd727f7e0615764cb234478beaeec3837aaebe
-size 237082452
diff --git a/config.json b/config.json
index 97e9aa6fa3791e8c7f8878b4d46d2e14a68a2d8b..5bdcb06b0643c774fcc5377df88b4a9b8264f2d6 100644
--- a/config.json
+++ b/config.json
@@ -45,7 +45,7 @@
   "ultracode": {
     "format": "raw-safetensors/1",
     "exported_from": "model.onnx",
-    "onnx_sha256": "73556d636633563bd0688d52899c475ff61a48f0687e8c48703ee4b9bc74d135",
+    "onnx_sha256": "9189bfedd376d2a08acd18e7b490000d5f78458c3e4388d1089704319a115840",
     "head": "entity_pool",
     "position_ids": "roberta",
     "pooling": "mean of the last hidden state over the tokens equal to each marker id; concat(E1, E2) -> classifier",
diff --git a/manifest.json b/manifest.json
deleted file mode 100644
index a0e1c6a3c1e7c6ce6185ffe637a58e0c97eb3aac..0000000000000000000000000000000000000000
--- a/manifest.json
+++ /dev/null
@@ -1,17 +0,0 @@
-{
-  "model_id": "code-daemon-relation-v1",
-  "dimension": 4,
-  "max_tokens": 256,
-  "quantization": "fp16",
-  "targets": [
-    "openvino"
-  ],
-  "runtime_tags": {
-    "trt": "trt11.3",
-    "ov": "ov2026.4",
-    "tvm": "tvm0.25",
-    "mlx_dir": "model_gpu_mlx0.32"
-  },
-  "compiled_at": "2026-09-24T02:28:50Z",
-  "compiled_by": "models/_compile"
-}
diff --git a/model.onnx b/model.onnx
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+++ b/model.onnx.data
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diff --git a/model.safetensors b/model.safetensors
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diff --git a/model_gpu_mlx0.32/config.json b/model_gpu_mlx0.32/config.json
deleted file mode 100644
index 97e9aa6fa3791e8c7f8878b4d46d2e14a68a2d8b..0000000000000000000000000000000000000000
--- a/model_gpu_mlx0.32/config.json
+++ /dev/null
@@ -1,57 +0,0 @@
-{
-  "add_cross_attention": false,
-  "architectures": [
-    "XLMRobertaForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "bos_token_id": 0,
-  "classifier_dropout": null,
-  "custom_head": "entity_start_marker_meanmask (concat E1,E2 -> Linear); [CLS] is not read",
-  "dtype": "float32",
-  "eos_token_id": 2,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 384,
-  "id2label": {
-    "0": "NO_RELATION",
-    "1": "semantically_similar_to",
-    "2": "supersedes_or_conflicts",
-    "3": "depends_on"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 1536,
-  "is_decoder": false,
-  "label2id": {
-    "NO_RELATION": 0,
-    "semantically_similar_to": 1,
-    "supersedes_or_conflicts": 2,
-    "depends_on": 3
-  },
-  "layer_norm_eps": 1e-05,
-  "max_position_embeddings": 514,
-  "model_type": "xlm-roberta",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "num_labels": 4,
-  "pad_token_id": 1,
-  "position_embedding_type": "absolute",
-  "sbert_ce_default_activation_function": "torch.nn.modules.linear.Identity",
-  "tie_word_embeddings": true,
-  "transformers_version": "5.1.0",
-  "type_vocab_size": 1,
-  "ultracode_note": "Inference artefact is model.onnx (inputs: input_ids, attention_mask; output: logits[batch, 4]). Feed the pair as (empty query, marked passage).",
-  "use_cache": true,
-  "vocab_size": 250006,
-  "ultracode": {
-    "format": "raw-safetensors/1",
-    "exported_from": "model.onnx",
-    "onnx_sha256": "73556d636633563bd0688d52899c475ff61a48f0687e8c48703ee4b9bc74d135",
-    "head": "entity_pool",
-    "position_ids": "roberta",
-    "pooling": "mean of the last hidden state over the tokens equal to each marker id; concat(E1, E2) -> classifier",
-    "entity_marker_ids": [
-      250002,
-      250004
-    ]
-  }
-}
diff --git a/model_gpu_mlx0.32/mlx_config.json b/model_gpu_mlx0.32/mlx_config.json
deleted file mode 100644
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--- a/model_gpu_mlx0.32/mlx_config.json
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-  "quantize": "none",
-  "format": "mlx-safetensors",
-  "prep_version": 2,
-  "head": "entity_pool",
-  "num_attention_heads": 12
-}
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@@ -11,7 +11,6 @@
     "[/E2]"
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   "is_local": false,
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   "mask_token": "<mask>",
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