@@ -95,6 +95,24 @@ become available.
9595 <td style="text-align: center;">✅</td>
9696 <td><code>lmms-lab/LLaVA-OneVision-Data</code>, <code>Aeala/ShareGPT_Vicuna_unfiltered</code></td>
9797 </tr>
98+ <tr>
99+ <td><strong>HuggingFace-MTBench</strong></td>
100+ <td style="text-align: center;">✅</td>
101+ <td style="text-align: center;">✅</td>
102+ <td><code>philschmid/mt-bench</code></td>
103+ </tr>
104+ <tr>
105+ <td><strong>HuggingFace-Blazedit</strong></td>
106+ <td style="text-align: center;">✅</td>
107+ <td style="text-align: center;">✅</td>
108+ <td><code>vdaita/edit_5k_char</code>, <code>vdaita/edit_10k_char</code></td>
109+ </tr>
110+ <tr>
111+ <td><strong>Spec Bench</strong></td>
112+ <td style="text-align: center;">✅</td>
113+ <td style="text-align: center;">✅</td>
114+ <td><code>wget https://raw.githubusercontent.com/hemingkx/Spec-Bench/refs/heads/main/data/spec_bench/question.jsonl</code></td>
115+ </tr>
98116 <tr>
99117 <td><strong>Custom</strong></td>
100118 <td style="text-align: center;">✅</td>
@@ -239,6 +257,43 @@ vllm bench serve \
239257 --num-prompts 2048
240258```
241259
260+ ### Spec Bench Benchmark with Speculative Decoding
261+
262+ ``` bash
263+ VLLM_USE_V1=1 vllm serve meta-llama/Meta-Llama-3-8B-Instruct \
264+ --speculative-config $' {"method": "ngram",
265+ "num_speculative_tokens": 5, "prompt_lookup_max": 5,
266+ "prompt_lookup_min": 2}'
267+ ```
268+
269+ [ SpecBench dataset] ( https://github.com/hemingkx/Spec-Bench )
270+
271+ Run all categories:
272+
273+ ``` bash
274+ # Download the dataset using:
275+ # wget https://raw.githubusercontent.com/hemingkx/Spec-Bench/refs/heads/main/data/spec_bench/question.jsonl
276+
277+ vllm bench serve \
278+ --model meta-llama/Meta-Llama-3-8B-Instruct \
279+ --dataset-name spec_bench \
280+ --dataset-path " <YOUR_DOWNLOADED_PATH>/data/spec_bench/question.jsonl" \
281+ --num-prompts -1
282+ ```
283+
284+ Available categories include ` [writing, roleplay, reasoning, math, coding, extraction, stem, humanities, translation, summarization, qa, math_reasoning, rag] ` .
285+
286+ Run only a specific category like "summarization":
287+
288+ ``` bash
289+ vllm bench serve \
290+ --model meta-llama/Meta-Llama-3-8B-Instruct \
291+ --dataset-name spec_bench \
292+ --dataset-path " <YOUR_DOWNLOADED_PATH>/data/spec_bench/question.jsonl" \
293+ --num-prompts -1
294+ --spec-bench-category " summarization"
295+ ```
296+
242297### Other HuggingFaceDataset Examples
243298
244299``` bash
@@ -295,6 +350,18 @@ vllm bench serve \
295350 --num-prompts 80
296351```
297352
353+ ` vdaita/edit_5k_char ` or ` vdaita/edit_10k_char ` :
354+
355+ ``` bash
356+ vllm bench serve \
357+ --model Qwen/QwQ-32B \
358+ --dataset-name hf \
359+ --dataset-path vdaita/edit_5k_char \
360+ --num-prompts 90 \
361+ --blazedit-min-distance 0.01 \
362+ --blazedit-max-distance 0.99
363+ ```
364+
298365### Running With Sampling Parameters
299366
300367When using OpenAI-compatible backends such as ` vllm ` , optional sampling
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