A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 14, 23:45 UTC
Add Unsloth to RLHF.md (#21636)
Daniel Han committed
Jul 25, 2025 at 17:06 UTC
41d3082c416897092bc924bc341e86b3e49728ee
1 file changed
+5
-1
docs/training/rlhf.md
+5
-1
@@ -2,10 +2,14 @@
2
3
Reinforcement Learning from Human Feedback (RLHF) is a technique that fine-tunes language models using human-generated preference data to align model outputs with desired behaviors.
4
5
-vLLM can be used to generate the completions for RLHF. The best way to do this is with libraries like [TRL](https://github.com/huggingface/trl), [OpenRLHF](https://github.com/OpenRLHF/OpenRLHF) and [verl](https://github.com/volcengine/verl).
5
+vLLM can be used to generate the completions for RLHF. Some ways to do this include using libraries like [TRL](https://github.com/huggingface/trl), [OpenRLHF](https://github.com/OpenRLHF/OpenRLHF), [verl](https://github.com/volcengine/verl) and [unsloth](https://github.com/unslothai/unsloth).
6
7
See the following basic examples to get started if you don't want to use an existing library:
8
9
- [Training and inference processes are located on separate GPUs (inspired by OpenRLHF)](../examples/offline_inference/rlhf.md)
10
- [Training and inference processes are colocated on the same GPUs using Ray](../examples/offline_inference/rlhf_colocate.md)
11
- [Utilities for performing RLHF with vLLM](../examples/offline_inference/rlhf_utils.md)
12
+
13
+See the following notebooks showing how to use vLLM for GRPO:
14
+
15
+- [Qwen-3 4B GRPO using Unsloth + vLLM](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_(4B)-GRPO.ipynb)