Update README.md
Browse files
README.md
CHANGED
|
@@ -34,18 +34,18 @@ For all samples, the response portion was regenerated using the target model `op
|
|
| 34 |
## 🚀 Quick Start
|
| 35 |
|
| 36 |
### SGLang
|
| 37 |
-
DFlash is now supported on SGLang. And vLLM integration is currently in progress.
|
| 38 |
|
| 39 |
#### Installation
|
| 40 |
```bash
|
| 41 |
uv pip install "git+https://github.com/sgl-project/sglang.git@refs/pull/20547/head#subdirectory=python"
|
| 42 |
```
|
| 43 |
|
| 44 |
-
####
|
| 45 |
```bash
|
| 46 |
-
|
| 47 |
-
export
|
| 48 |
-
export
|
|
|
|
| 49 |
|
| 50 |
python -m sglang.launch_server \
|
| 51 |
--model-path openai/gpt-oss-20b \
|
|
@@ -58,6 +58,56 @@ python -m sglang.launch_server \
|
|
| 58 |
--trust-remote-code
|
| 59 |
```
|
| 60 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 61 |
## Evaluation
|
| 62 |
We use a **block size of 8 (7 draft tokens)** during speculation. DFlash consistently achieves high acceptance lengths and speedups across different concurrency levels. All experiments are conducted using **SGLang** on a single **H200 GPU**.
|
| 63 |
|
|
|
|
| 34 |
## 🚀 Quick Start
|
| 35 |
|
| 36 |
### SGLang
|
|
|
|
| 37 |
|
| 38 |
#### Installation
|
| 39 |
```bash
|
| 40 |
uv pip install "git+https://github.com/sgl-project/sglang.git@refs/pull/20547/head#subdirectory=python"
|
| 41 |
```
|
| 42 |
|
| 43 |
+
#### Launch Server
|
| 44 |
```bash
|
| 45 |
+
# Optional: enable schedule overlapping (experimental, may not be stable)
|
| 46 |
+
# export SGLANG_ENABLE_SPEC_V2=1
|
| 47 |
+
# export SGLANG_ENABLE_DFLASH_SPEC_V2=1
|
| 48 |
+
# export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
|
| 49 |
|
| 50 |
python -m sglang.launch_server \
|
| 51 |
--model-path openai/gpt-oss-20b \
|
|
|
|
| 58 |
--trust-remote-code
|
| 59 |
```
|
| 60 |
|
| 61 |
+
#### Usage
|
| 62 |
+
|
| 63 |
+
```python
|
| 64 |
+
from openai import OpenAI
|
| 65 |
+
|
| 66 |
+
client = OpenAI(base_url="http://localhost:30000/v1", api_key="EMPTY")
|
| 67 |
+
|
| 68 |
+
response = client.chat.completions.create(
|
| 69 |
+
model="openai/gpt-oss-20b",
|
| 70 |
+
messages=[{"role": "user", "content": "Write a quicksort in Python."}],
|
| 71 |
+
max_tokens=2048,
|
| 72 |
+
temperature=0.0,
|
| 73 |
+
)
|
| 74 |
+
print(response.choices[0].message.content)
|
| 75 |
+
```
|
| 76 |
+
|
| 77 |
+
### vLLM
|
| 78 |
+
|
| 79 |
+
#### Installation
|
| 80 |
+
|
| 81 |
+
```bash
|
| 82 |
+
uv pip install vllm
|
| 83 |
+
uv pip install -U vllm --torch-backend=auto --extra-index-url https://wheels.vllm.ai/nightly
|
| 84 |
+
```
|
| 85 |
+
|
| 86 |
+
#### Launch Server
|
| 87 |
+
|
| 88 |
+
```bash
|
| 89 |
+
vllm serve openai/gpt-oss-20b \
|
| 90 |
+
--speculative-config '{"method": "dflash", "model": "z-lab/gpt-oss-20b-DFlash", "num_speculative_tokens": 7}' \
|
| 91 |
+
--attention-backend flash_attn \
|
| 92 |
+
--max-num-batched-tokens 32768
|
| 93 |
+
```
|
| 94 |
+
|
| 95 |
+
#### Usage
|
| 96 |
+
|
| 97 |
+
```python
|
| 98 |
+
from openai import OpenAI
|
| 99 |
+
|
| 100 |
+
client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
|
| 101 |
+
|
| 102 |
+
response = client.chat.completions.create(
|
| 103 |
+
model="openai/gpt-oss-20b",
|
| 104 |
+
messages=[{"role": "user", "content": "Write a quicksort in Python."}],
|
| 105 |
+
max_tokens=2048,
|
| 106 |
+
temperature=0.0,
|
| 107 |
+
)
|
| 108 |
+
print(response.choices[0].message.content)
|
| 109 |
+
```
|
| 110 |
+
|
| 111 |
## Evaluation
|
| 112 |
We use a **block size of 8 (7 draft tokens)** during speculation. DFlash consistently achieves high acceptance lengths and speedups across different concurrency levels. All experiments are conducted using **SGLang** on a single **H200 GPU**.
|
| 113 |
|