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rmccorm4 merged 1 commit into from
Jun 11, 2025
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docs: Add note about ignore_eos for MTP #1475

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Add note about ignore_eos for MTP
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@rmccorm4
rmccorm4 committed Jun 11, 2025
commit 25eb20f7a3926899d7fa6af1a851c0d09cefc1d0
12 changes: 7 additions & 5 deletions examples/tensorrt_llm/README.md
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Expand Up @@ -129,14 +129,15 @@ cd /workspace/examples/tensorrt_llm
dynamo serve graphs.disagg_router:Frontend -f ./configs/disagg_router.yaml
```

#### Aggregated serving with Multi-Token Prediction(MTP) and DeepSeek R1
#### Aggregated serving with Multi-Token Prediction (MTP) and DeepSeek R1
```bash
cd /workspace/examples/tensorrt_llm
dynamo serve graphs.agg:Frontend -f configs/deepseek_r1/mtp/mtp_agg.yaml
```

Notes:
- There is a noticeable latency for the first two inference requests. Please send warm-up requests before starting the benchmark.
- MTP performance may vary depending on the acceptance rate of predicted tokens, which is dependent on the dataset or queries used while benchmarking
- MTP performance may vary depending on the acceptance rate of predicted tokens, which is dependent on the dataset or queries used while benchmarking. Additionally, `ignore_eos` should generally be omitted or set to `false` when using MTP to avoid speculating garbage outputs and getting unrealistic acceptance rates.

#### Multi-Node Disaggregated Serving

Expand Down Expand Up @@ -233,7 +234,7 @@ Notes:
unset SLURM_JOBID SLURM_JOB_ID SLURM_NODELIST
```

#### Multi-Node Disaggregated Serving with Multi-Token Prediction(MTP) and DeepSeek R1
#### Multi-Node Disaggregated Serving with Multi-Token Prediction (MTP) and DeepSeek R1

Most of the steps remain the same as the above example, but this time we will have `dynamo serve` point to different config files that contains the MTP configurations

Expand Down Expand Up @@ -268,8 +269,9 @@ dynamo serve components.prefill_worker:TensorRTLLMPrefillWorker -f configs/deeps
```

Notes:
- There is a noticeable latency for the first four inference requests. Please send warm-up requests before starting the benchmark.
- MTP performance may vary depending on the acceptance rate of predicted tokens, which is dependent on the dataset or queries used while benchmarking
- There is a noticeable latency for the first two inference requests. Please send warm-up requests before starting the benchmark.
- MTP performance may vary depending on the acceptance rate of predicted tokens, which is dependent on the dataset or queries used while benchmarking. Additionally, `ignore_eos` should generally be omitted or set to `false` when using MTP to avoid speculating garbage outputs and getting unrealistic acceptance rates.


### Client

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