# \[RFC\] Transformers Pipeline v2

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**Category:** 🤗Transformers\
**Created:** [September 21, 2020, 10:11am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Frfc-transformers-pipeline-v2%2F1209 "2020-09-21T10:11:04Z")\
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**Author:** ![dataiku](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/dataiku/32/2634_2.png) [@dataiku](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fdataiku)%5C
**Post date:** [October 14, 2020, 9:53am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Frfc-transformers-pipeline-v2%2F1209%2F5 "2020-10-14T09:53:33Z")

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Hi,

Just an aparté on ONNX inference (cross-post from [Supporting ONNX optimized models](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fsupporting-onnx-optimized-models%2F891))

I’d be interested in an `nlp = pipeline("sentiment-analysis", onnx=True)` pipeline like @valhalla created, where the ONNX files are hosted on the model hub and stored in the transformers cache.

My use case is fast inference of pre-trained models on embedded applications (no network connection).

Cheers,

Alex

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