Create README.md

README.md

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+---
+license: mit
+base_model:
+- deepseek-ai/DeepSeek-R1-0528
+---
+
+
+# Model Overview
+
+- **Model Architecture:** DeepSeek-R1-0528
+  - **Input:** Text
+  - **Output:** Text
+- **Supported Hardware Microarchitecture:** AMD MI350/MI355
+- **ROCm**: 7.0
+- **PyTorch**: 2.8.0
+- **Transformers**: 4.53.0
+- **Operating System(s):** Linux
+- **Inference Engine:** [SGLang](https://docs.sglang.ai/)/[vLLM](https://docs.vllm.ai/en/latest/)
+- **Model Optimizer:** [AMD-Quark](https://quark.docs.amd.com/latest/index.html) (V0.10)
+  - **Weight quantization:** OCP MXFP4, Static
+  - **Activation quantization:** OCP MXFP4, Dynamic
+- **Calibration Dataset:** [Pile](https://huggingface.co/datasets/mit-han-lab/pile-val-backup)
+
+This model was built with deepseek-ai DeepSeek-R1-0528 model by applying [AMD-Quark](https://quark.docs.amd.com/latest/index.html) for MXFP4 quantization.
+
+# Model Quantization
+
+The model was quantized from [deepseek-ai/DeepSeek-R1-0528](https://huggingface.co/deepseek-ai/DeepSeek-R1-0528) using [AMD-Quark](https://quark.docs.amd.com/latest/index.html). Both weights and activations were quantized to MXFP4 format. 
+
+**Preprocessing requirement:**
+
+Before executing the quantization script below, the original FP8 model must first be dequantized to BFloat16.
+You can either perform the dequantization manually using this [conversion script](https://github.com/deepseek-ai/DeepSeek-V3/blob/main/inference/fp8_cast_bf16.py), or use the pre-converted BFloat16 model available at [amd/DeepSeek-R1-0528-BF16](https://huggingface.co/amd/DeepSeek-R1-0528-BF16).
+
+**Quantization scripts:**
+```
+cd Quark/examples/torch/language_modeling/llm_ptq/
+exclude_layers="*lm_head model.layers.61.*"
+python3 quantize_quark.py --model_dir $MODEL_DIR \
+                          --quant_scheme w_mxfp4_a_mxfp4 \
+                          --group_size 32 \
+                          --num_calib_data 128 \
+                          --exclude_layers $exclude_layers \
+                          --skip_evaluation \
+                          --multi_gpu \
+                          --model_export hf_format \
+                          --output_dir amd/DeepSeek-R1-0528-MXFP4-V2
+```
+
+# Deployment
+
+This model can be deployed efficiently using the [SGLang](https://docs.sglang.ai/) and [vLLM](https://docs.vllm.ai/en/latest/) backends.
+
+## Evaluation
+
+The model was evaluated on AIME24, and GSM8K benchmarks using the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) framework. 
+
+### Accuracy
+
+<table>
+  <tr>
+   <td><strong>Benchmark</strong>
+   </td>
+   <td><strong>DeepSeek-R1-0528-MXFP4-V2 (non MTP) </strong>
+   </td>
+   <td><strong>DeepSeek-R1-0528-MXFP4-V2 (MTP=3)</strong>
+   </td>
+  </tr>
+  <tr>
+   <td>AIME24 
+   </td>
+   <td>80.00
+   </td>
+   <td>83.33
+   </td>
+  </tr>
+  <tr>
+   <td>GSM8K 
+   </td>
+   <td>95.00
+   </td>
+   <td>95.30
+   </td>
+  </tr>
+</table>
+
+### Reproduction
+
+The results of AIME24 and GSM8K, were obtained using forked [lm-evaluation-harness](https://github.com/BowenBao/lm-evaluation-harness/tree/cot).
+
+### Launch Server
+```
+#!/bin/bash
+MODEL=/models/amd/DeepSeek-R1-0528-MXFP4-V2
+LOG="sglang-serving.log"
+
+SGLANG_AITER_MLA_PERSIST=1 \
+python3 -m sglang.launch_server \
+--model-path $MODEL \
+--tensor-parallel-size 8 \
+--trust-remote-code \
+--chunked-prefill-size 131072 \
+--host 0.0.0.0 \
+--port 8321 \
+--disable-radix-cache \
+--mem-fraction-static 0.8 \
+--max-running-requests 64 \
+--attention-backend aiter 2>&1 | tee $LOG
+```
+
+### AIME24
+```
+lm_eval --model local-completions \
+    --model_args model=/models/amd/DeepSeek-R1-0528-MXFP4-V2,base_url=http://0.0.0.0:8321/v1/completions,num_concurrent=999999,timeout=999999,tokenized_requests=False,max_length=32000,temperature=0.6,top_p=0.95 \
+    --tasks aime24 \
+    --num_fewshot 0 \
+    --gen_kwargs "do_sample=True,temperature=0.6,top_p=0.95,max_tokens=32000" \
+    --batch_size auto 2>&1 | tee aime24.log
+```
+
+### GSM8K
+```
+lm_eval --model local-completions \
+    --model_args model=/models/amd/DeepSeek-R1-0528-MXFP4-V2,base_url=http://0.0.0.0:8321/v1/completions,num_concurrent=256,max_retries=10,max_gen_toks=2048,tokenized_requests=False \
+    --tasks gsm8k \
+    --num_fewshot 5 \
+    --batch_size auto 2>&1 | tee gsm8k.log
+```
+
+# License
+Modifications Copyright(c) 2025 Advanced Micro Devices, Inc. All rights reserved.