pytorch
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diff --git a/‎torchtitan/models/deepseek_v3/README.md‎
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diff --git a/‎torchtitan/models/deepseek_v3/__init__.py‎
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@@ -7,4 +7,5 @@
 
 # Import the built-in models here so that the corresponding register_model_spec()
 # will be called.
+import torchtitan.models.deepseek_v3  # noqa: F401
 import torchtitan.models.llama3  # noqa: F401
@@ -0,0 +1,54 @@
+# DeepSeek-V3 in TorchTitan
+
+DeepSeek-V3 is a Mixture-of-Experts (MoE) transformer model with Multi-head Latent Attention (MLA) architecture.
+
+## Setup
+
+### Download Tokenizer
+
+```bash
+# DeepSeek tokenizer (automatically downloads tokenizer.json and tokenizer_config.json)
+python scripts/download_tokenizer.py --repo_id deepseek-ai/DeepSeek-V3
+```
+
+## Training
+
+### Debug Training
+
+```bash
+# Quick debug run with small model
+CONFIG_FILE="./torchtitan/models/deepseek_v3/train_configs/debug_model.toml" ./run_train.sh
+```
+
+### Full Model Training
+
+```bash
+# 16B parameter model: adapted from older 16B parameter model from https://huggingface.co/deepseek-ai/deepseek-moe-16b-base
+CONFIG_FILE="./torchtitan/models/deepseek_v3/train_configs/deepseek_v3_16b.toml" ./run_train.sh
+```
+
+```bash
+# 671B parameter model
+CONFIG_FILE="./torchtitan/models/deepseek_v3/train_configs/deepseek_v3_671b.toml" ./run_train.sh
+```
+
+
+## Supported Features
+- FSDP, HSDP
+- Activation checkpointing
+- Tensor Parallel (TP)
+- Expert Parallel (EP)
+
+
+## To be added
+- Modeling
+    - Merge DeepSeek-V3 and Llama4 MoE common components
+    - Attention Layer: need to pass softmax_scale to sdpa() to support scaling
+- Parallelism
+    - Context Parallel support for DeepSeek-V3
+    - PP support for DeepSeek-V3
+- torch.compile
+- Quantization
+- Testing
+    - perfomance and loss converging tests
+    - CI integration
@@ -0,0 +1,126 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+#
+# Copyright (c) Meta Platforms, Inc. All Rights Reserved.
+
+from torchtitan.components.loss import build_cross_entropy_loss
+from torchtitan.components.lr_scheduler import build_lr_schedulers
+from torchtitan.components.tokenizer import build_hf_tokenizer
+from torchtitan.datasets.hf_datasets import build_hf_dataloader
+from torchtitan.experiments.llama4.optimizer import build_llama4_optimizers
+
+from torchtitan.protocols.train_spec import register_train_spec, TrainSpec
+
+from .infra.parallelize import parallelize_deepseekv3
+from .model.args import DeepSeekV3ModelArgs
+from .model.model import DeepSeekV3Model
+
+__all__ = [
+    "parallelize_deepseekv3",
+    "DeepseekV3ModelArgs",
+    "DeepseekV3Model",
+    "deepseekv3_configs",
+]
+
+
+deepseekv3_configs = {
+    "debugmodel": DeepSeekV3ModelArgs(
+        vocab_size=102400,
+        dim=256,
+        inter_dim=1024,
+        moe_inter_dim=256,
+        n_layers=3,
+        n_dense_layers=1,
+        n_heads=16,
+        n_routed_experts=8,
+        n_shared_experts=2,
+        n_activated_experts=3,
+        route_scale=1.0,
+        q_lora_rank=0,
+        kv_lora_rank=512,
+        qk_nope_head_dim=128,
+        qk_rope_head_dim=64,
+        v_head_dim=128,
+        mscale=0.70,
+    ),
+    "16B": DeepSeekV3ModelArgs(
+        vocab_size=102400,
+        dim=2048,
+        inter_dim=10944,
+        moe_inter_dim=1408,
+        n_layers=27,
+        n_dense_layers=1,
+        n_heads=16,
+        n_routed_experts=64,
+        n_shared_experts=2,
+        n_activated_experts=6,
+        route_scale=1.0,
+        q_lora_rank=0,
+        kv_lora_rank=512,
+        qk_nope_head_dim=128,
+        qk_rope_head_dim=64,
+        v_head_dim=128,
+        mscale=0.70,
+    ),
+    "236B": DeepSeekV3ModelArgs(
+        vocab_size=102400,
+        dim=5120,
+        inter_dim=12288,
+        moe_inter_dim=1536,
+        n_layers=60,
+        n_dense_layers=1,
+        n_heads=128,
+        n_routed_experts=160,
+        n_shared_experts=2,
+        n_activated_experts=6,
+        n_expert_groups=8,
+        n_limited_groups=3,
+        route_scale=16.0,
+        q_lora_rank=1536,
+        kv_lora_rank=512,
+        qk_nope_head_dim=128,
+        qk_rope_head_dim=64,
+        v_head_dim=128,
+    ),
+    "671B": DeepSeekV3ModelArgs(
+        vocab_size=129280,
+        dim=7168,
+        inter_dim=18432,
+        moe_inter_dim=2048,
+        n_layers=61,
+        n_dense_layers=3,
+        n_heads=128,
+        n_routed_experts=256,
+        n_shared_experts=1,
+        n_activated_experts=8,
+        n_expert_groups=8,
+        n_limited_groups=4,
+        route_scale=2.5,
+        score_func="sigmoid",
+        q_lora_rank=1536,
+        kv_lora_rank=512,
+        qk_nope_head_dim=128,
+        qk_rope_head_dim=64,
+        v_head_dim=128,
+        dtype="fp8",
+    ),
+}
+
+
+register_train_spec(
+    TrainSpec(
+        name="deepseek_v3",
+        cls=DeepSeekV3Model,
+        config=deepseekv3_configs,
+        parallelize_fn=parallelize_deepseekv3,
+        pipelining_fn=None,
+        build_optimizers_fn=build_llama4_optimizers,  # use optimizer hooks to update expert weights
+        build_lr_schedulers_fn=build_lr_schedulers,
+        build_dataloader_fn=build_hf_dataloader,
+        build_tokenizer_fn=build_hf_tokenizer,
+        build_loss_fn=build_cross_entropy_loss,
+    )
+)