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config.json

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+{
+  "architectures": [
+    "DSparkDraftModel"
+  ],
+  "auto_map": {
+    "": "config.DSparkSpeculatorConfig"
+  },
+  "aux_hidden_state_layer_ids": [
+    2,
+    12,
+    21
+  ],
+  "block_size": 8,
+  "confidence_head_with_markov": true,
+  "draft_vocab_size": 8192,
+  "dtype": "bfloat16",
+  "enable_confidence_head": true,
+  "markov_head_type": "vanilla",
+  "markov_rank": 256,
+  "mask_token_id": 158685,
+  "sliding_window_non_causal": false,
+  "speculators_config": {
+    "algorithm": "dspark",
+    "default_proposal_method": "greedy",
+    "proposal_methods": [
+      {
+        "accept_tolerance": 0.0,
+        "proposal_type": "greedy",
+        "speculative_tokens": 7,
+        "verifier_accept_k": 1
+      }
+    ],
+    "verifier": {
+      "architectures": [
+        "Qwen2ForCausalLM"
+      ],
+      "name_or_path": "yuekai/Fun-CosyVoice3-0.5B-2512-LLM-HF"
+    }
+  },
+  "speculators_model_type": "dspark",
+  "speculators_version": "0.7.0.dev81",
+  "target_hidden_size": null,
+  "tie_word_embeddings": false,
+  "transformer_layer_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": null,
+    "eos_token_id": null,
+    "head_dim": 64,
+    "hidden_act": "silu",
+    "hidden_size": 896,
+    "initializer_range": 0.02,
+    "intermediate_size": 4864,
+    "layer_types": [
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention"
+    ],
+    "max_position_embeddings": 32768,
+    "max_window_layers": 28,
+    "model_type": "qwen3",
+    "num_attention_heads": 14,
+    "num_hidden_layers": 3,
+    "num_key_value_heads": 2,
+    "pad_token_id": null,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+      "rope_theta": 1000000.0,
+      "rope_type": "default"
+    },
+    "sliding_window": 2048,
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "use_sliding_window": true,
+    "vocab_size": 158720
+  },
+  "transformers_version": "5.8.1"
+}

config.py

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+from typing import Literal
+
+from pydantic import Field
+
+from speculators import SpeculatorModelConfig
+from speculators.models.dflash.config import DFlashSpeculatorConfig
+
+__all__ = [
+    "DSparkSpeculatorConfig",
+]
+
+
+@SpeculatorModelConfig.register("dspark")
+class DSparkSpeculatorConfig(DFlashSpeculatorConfig):
+    """DFlash config plus a Markov logit-bias head and a confidence head.
+
+    The Markov head lets each draft position condition on previously sampled
+    tokens within the block; the confidence head predicts the per-position
+    acceptance probability. All DFlash fields are inherited unchanged.
+    """
+
+    speculators_model_type: Literal["dspark"] = "dspark"  # type: ignore[assignment]
+    architectures: list[str] = Field(
+        default_factory=lambda: ["DSparkSpeculator"],
+        description="Model architectures that can load these weights",
+    )
+
+    # Sequential (Markov) head.
+    markov_rank: int = Field(
+        default=256,
+        description=(
+            "Low-rank dimension of the Markov logit-bias factorization B = W1 @ W2. "
+            "Set to 0 to disable the sequential head (pure DFlash drafting)."
+        ),
+    )
+    markov_head_type: Literal["vanilla", "gated", "rnn"] = Field(
+        default="vanilla",
+        description=(
+            "Sequential head variant: 'vanilla' (first-order Markov bias), 'gated' "
+            "(hidden-gated bias), or 'rnn' (recurrent state over the block)."
+        ),
+    )
+
+    # Confidence head.
+    enable_confidence_head: bool = Field(
+        default=True,
+        description="Whether to attach the per-position acceptance-probability head.",
+    )
+    confidence_head_with_markov: bool = Field(
+        default=True,
+        description=(
+            "Concatenate the Markov previous-token embedding with the backbone "
+            "hidden state as the confidence-head input."
+        ),
+    )

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4bd5706d21aef622c3b644668549bc601a656fdfdde3f26886bdb6e1ec0d03b8
+size 479084938