|
@@ -241,7 +241,7 @@ After supervised fine-tuning, RLHF is a step used to align the LLM's answers wit
|
|
|
* [Illustration RLHF](https://huggingface.co/blog/rlhf) by Hugging Face: Introduction to RLHF with reward model training and fine-tuning with reinforcement learning.
|
|
|
* [Preference Tuning LLMs](https://huggingface.co/blog/pref-tuning) by Hugging Face: Comparison of the DPO, IPO, and KTO algorithms to perform preference alignment.
|
|
|
* [LLM Training: RLHF and Its Alternatives](https://magazine.sebastianraschka.com/p/llm-training-rlhf-and-its-alternatives) by Sebastian Rashcka: Overview of the RLHF process and alternatives like RLAIF.
|
|
|
-* [Fine-tune Mistral-7b with DPO](https://huggingface.co/blog/dpo-trl): Tutorial to fine-tune a Mistral-7b model with DPO and reproduce [NeuralHermes-2.5](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B).
|
|
|
+* [Fine-tune Mistral-7b with DPO](https://mlabonne.github.io/blog/posts/Fine_tune_Mistral_7b_with_DPO.html): Tutorial to fine-tune a Mistral-7b model with DPO and reproduce [NeuralHermes-2.5](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B).
|
|
|
|
|
|
---
|
|
|
### 6. Evaluation
|