Duplicate from GODELEV/Rose-1.5-Mini

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+language: en
+tags:
+- causal-lm
+- gqa
+- qk-norm
+- rope
+- swiglu
+- refresh-gate
+- rose-x1
+license: apache-2.0
+---
+
+# Rose-1.5-Mini
+
+Rose X1.5 SLM (98.6M params).
+
+## Architecture
+| Property | Value |
+|---|---|
+| Layers | 22 |
+| Hidden | 576 |
+| Heads | 9 (kv=3) |
+| QK Norm | True |
+| Refresh Gate | [6, 13] |
+| Params | 98.612M |
+
+## Training
+- Tokens: 160,392,960,000
+- Val PPL: 5.29
+- Optimizer: muon_adamw

config.json

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+{
+  "architectures": [
+    "RoseX15ForCausalLM"
+  ],
+  "model_type": "rose_x1_5",
+  "auto_map": {
+    "AutoConfig": "configuration_rose_x1_5.RoseX15Config",
+    "AutoModelForCausalLM": "modeling_rose_x1_5.RoseX15ForCausalLM"
+  },
+  "vocab_size": 32768,
+  "hidden_size": 576,
+  "intermediate_size": 1532,
+  "num_hidden_layers": 22,
+  "num_attention_heads": 9,
+  "num_key_value_heads": 3,
+  "head_dim": 64,
+  "max_position_embeddings": 4096,
+  "hidden_act": "silu",
+  "rms_norm_eps": 1e-06,
+  "attention_bias": false,
+  "mlp_bias": false,
+  "attention_dropout": 0.0,
+  "tie_word_embeddings": true,
+  "rope_theta": 100000.0,
+  "rope_scaling": null,
+  "use_qk_norm": true,
+  "use_xsa": true,
+  "refresh_gate_enabled": true,
+  "refresh_gate_inject_layers": [
+    6,
+    13
+  ],
+  "refresh_gate_kernel_size": 9,
+  "mup_enabled": false,
+  "mup_base_hidden_size": null,
+  "mup_width_mult": null,
+  "bos_token_id": 2,
+  "eos_token_id": 3,
+  "pad_token_id": 0,
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.0",
+  "use_cache": true,
+  "pretraining_tp": 1,
+  "initializer_range": 0.02
+}

configuration_rose_x1_5.py

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+"""Rose X1.5 model configuration."""
+from transformers import PretrainedConfig
+
+
+class RoseX15Config(PretrainedConfig):
+    """Configuration for the Rose X1.5 architecture.
+
+    Rose X1.5 extends the T-X4 family with:
+      - Grouped-Query Attention (GQA) with per-head QK-Norm
+      - Half-split RoPE
+      - SwiGLU MLP
+      - RMSNorm
+      - Exclusive Self Attention (XSA)
+      - Refresh Gate (gated re-injection of original token embedding)
+      - Tied word embeddings
+    """
+
+    model_type = "rose_x1_5"
+
+    def __init__(
+        self,
+        vocab_size=32768,
+        hidden_size=576,
+        num_hidden_layers=22,
+        num_attention_heads=9,
+        num_key_value_heads=3,
+        head_dim=64,
+        intermediate_size=1532,
+        max_position_embeddings=4096,
+        hidden_act="silu",
+        rms_norm_eps=1e-6,
+        attention_bias=False,
+        mlp_bias=False,
+        attention_dropout=0.0,
+        rope_theta=100000.0,
+        rope_scaling=None,
+        tie_word_embeddings=True,
+        # QK Norm
+        use_qk_norm=True,
+        # XSA (Exclusive Self Attention)
+        use_xsa=True,
+        # Refresh Gate
+        refresh_gate_enabled=True,
+        refresh_gate_inject_layers=None,
+        refresh_gate_kernel_size=9,
+        # muP (recorded for reproducibility; does not affect forward pass)
+        mup_enabled=False,
+        mup_base_hidden_size=None,
+        mup_width_mult=None,
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.num_key_value_heads = num_key_value_heads
+        self.head_dim = head_dim
+        self.intermediate_size = intermediate_size
+        self.max_position_embeddings = max_position_embeddings
+        self.hidden_act = hidden_act
+        self.rms_norm_eps = rms_norm_eps
+        self.attention_bias = attention_bias
+        self.mlp_bias = mlp_bias
+        self.attention_dropout = attention_dropout
+        self.rope_theta = rope_theta
+        self.rope_scaling = rope_scaling
+        # QK Norm
+        self.use_qk_norm = use_qk_norm
+        # XSA
+        self.use_xsa = use_xsa
+        # Refresh Gate
+        self.refresh_gate_enabled = refresh_gate_enabled
+        self.refresh_gate_inject_layers = (
+            list(refresh_gate_inject_layers)
+            if refresh_gate_inject_layers is not None
+            else [4, 9]
+        )
+        self.refresh_gate_kernel_size = refresh_gate_kernel_size
+        # muP (metadata only)
+        self.mup_enabled = mup_enabled
+        self.mup_base_hidden_size = mup_base_hidden_size
+        self.mup_width_mult = mup_width_mult
+        super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)

generation_config.json

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+{
+  "bos_token_id": 2,
+  "eos_token_id": 3
+}

logs/log_100000.jsonl

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logs/log_104000.jsonl

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logs/log_105000.jsonl

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logs/log_108000.jsonl

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logs/log_109000.jsonl

@@ -0,0 +1,52 @@
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logs/log_11000.jsonl

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logs/log_110000.jsonl

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logs/log_112000.jsonl

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logs/log_113000.jsonl

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logs/log_114000.jsonl

@@ -0,0 +1,52 @@
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logs/log_115000.jsonl

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logs/log_116000.jsonl

@@ -0,0 +1,154 @@
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logs/log_117000.jsonl

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logs/log_118000.jsonl

@@ -0,0 +1,256 @@
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logs/log_119000.jsonl

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logs/log_1200.jsonl

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logs/log_12000.jsonl

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logs/log_120000.jsonl

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logs/log_121000.jsonl

@@ -0,0 +1,154 @@
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logs/log_122000.jsonl

@@ -0,0 +1,205 @@
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logs/log_123000.jsonl

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logs/log_124000.jsonl

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logs/log_13000.jsonl

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logs/log_130000.jsonl

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logs/log_131000.jsonl

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logs/log_135000.jsonl

@@ -0,0 +1,52 @@
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logs/log_136000.jsonl

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logs/log_137000.jsonl

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logs/log_138000.jsonl

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logs/log_139000.jsonl

@@ -0,0 +1,256 @@
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