# Load\_dataset vs custom torch dataset

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**Category:** Beginners\
**Created:** [September 22, 2022, 6:52pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fload-dataset-vs-custom-torch-dataset%2F23504 "2022-09-22T18:52:00Z")\
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**Author:** ![j2hamster](https://avatars.discourse-cdn.com/v4/letter/j/bcef8e/32.png) [@j2hamster](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fj2hamster)%5C
**Post date:** [September 22, 2022, 6:52pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fload-dataset-vs-custom-torch-dataset%2F23504%2F1 "2022-09-22T18:52:00Z")

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I am new to HF and recently followed a fine tuning example where I tuned an NLP model for my own local csv data. In that example I had to put the data into a custom torch dataset to be fed to the trainer. I am looking at other examples of fine-tuning and I am seeing usage of a HF class called “load\_dataset” for local data where it appears to just take the data and do the transform for you. There appears to be no need to write my own Torch DataSet class. I am seeing that load\_dataset can handle images and audio too. If I am reading the code and the doc correctly, why would I ever need to write my own torch dataset for fine-tuning? Thanks