vllm-project · DarkLight1337 · Mar 15, 2025 · Mar 7, 2025 · Mar 8, 2025 · Mar 8, 2025
diff --git a/docs/source/features/spec_decode.md b/docs/source/features/spec_decode.md
@@ -162,7 +162,7 @@ A variety of speculative models of this type are available on HF hub:
 ## Speculating using EAGLE based draft models
 
 The following code configures vLLM to use speculative decoding where proposals are generated by
-an [EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency)](https://arxiv.org/pdf/2401.15077) based draft model. A more detailed example for offline mode, including how to extract request level acceptance rate, can be found [here](/examples/offline_inference/eagle.py).
+an [EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency)](https://arxiv.org/pdf/2401.15077) based draft model. A more detailed example for offline mode, including how to extract request level acceptance rate, can be found [here](https://github.com/vllm-project/vllm/blob/main/examples/offline_inference/eagle.py).
-an [EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency)](https://arxiv.org/pdf/2401.15077) based draft model. A more detailed example for offline mode, including how to extract request level acceptance rate, can be found [here](https://github.com/vllm-project/vllm/blob/main/examples/offline_inference/eagle.py).
+an [EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency)](https://arxiv.org/pdf/2401.15077) based draft model. A more detailed example for offline mode, including how to extract request level acceptance rate, can be found [here](<gh-file:examples/offline_inference/eagle.py>).
-an [EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency)](https://arxiv.org/pdf/2401.15077) based draft model. A more detailed example for offline mode, including how to extract request level acceptance rate, can be found [here](https://github.com/vllm-project/vllm/blob/main/examples/offline_inference/eagle.py).
+an [EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency)](https://arxiv.org/pdf/2401.15077) based draft model. A more detailed example for offline mode, including how to extract request level acceptance rate, can be found [here](<gh-file:examples/offline_inference/eagle.py>).
 
 ```python
 from vllm import LLM, SamplingParams