# Practical Industry usage example for Fine tuning

**URL:** <https://community.deeplearning.ai/t/practical-industry-usage-example-for-fine-tuning/883060>\
**Category:** Fine-tuning & RL for LLMs: Intro to Post-training\
**Tags:** week-module-1, dl-ai-learning-platform\
**Created:** [November 10, 2025, 12:57am UTC](https://community.deeplearning.ai/t/practical-industry-usage-example-for-fine-tuning/883060 "2025-11-10T00:57:25Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![jain.anshuman](https://avatars.discourse-cdn.com/v4/letter/j/a3d4f5/32.png) [@jain.anshuman](https://community.deeplearning.ai/u/jain.anshuman)\
**Post date:** [November 10, 2025, 12:57am UTC](https://community.deeplearning.ai/t/practical-industry-usage-example-for-fine-tuning/883060/1 "2025-11-10T00:57:25Z")

</div>

What are some industry examples on why you would fine tune a model. For example - if I have a large set of company specific ERP training documentation , can we fine tune a model with Q&A with that training documentation versus completely relying on RAG. What are some other real examples

---

<div class="post-metadata">

**Author:** ![balaji.ambresh](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/balaji.ambresh/32/128697_2.png) [@balaji.ambresh](https://community.deeplearning.ai/u/balaji.ambresh)\
**Post date:** [November 10, 2025, 3:30am UTC](https://community.deeplearning.ai/t/practical-industry-usage-example-for-fine-tuning/883060/2 "2025-11-10T03:30:57Z")

</div>

When it comes to image classification, we can fine-tune an existing model (especially when the current task has few examples or limited resources for exploring model architectures). Please see [this](https://en.wikipedia.org/wiki/Fine-tuning_(deep_learning)) link to learn a bit more on fine-tuning. [Deep learning specialization](https://www.coursera.org/specializations/deep-learning) does cover this topic as well.