How to load transformers pipeline from folder?

Question

According to here pipeline provides an interface to save a pretrained pipeline locally with a save_pretrained method. When I use it, I see a folder created with a bunch of json and bin files presumably for the tokenizer and the model.

But the documentation does not specify a load method. How does one initialize a pipeline using a locally saved pipeline?

Asked By: Layman

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Source

Answer 1

If you read the specification for save_pretrained, it simply states that it

Save[s] the pipeline’s model and tokenizer.

I’ve also given a slightly related answer here on how custom models and tokenizers can be loaded. Essentially, you can simply specify the specific models/paths in the pipeline:

from transformers import pipeline, AutoModel, AutoTokenizer

# Replace with your custom model of choice
model = AutoModel.from_pretrained('/path/to/your/model')
tokenizer = AutoTokenizer.from_pretrained('/path/to/your/tokenizer')

pipe = pipeline(task='summarization',  # replace with whatever task you have
                model=model,
                tokenizer=tokenizer)

Answered By: dennlinger

Answer 2

Apparently the default initialization works with local folders as well. So one can download a model like this:

pipe = pipeline("text-classification")
pipe.save_pretrained("my_local_path")

And later load it like

pipe = pipeline("text-classification", model = "my_local_path")

Answered By: Layman

How to load transformers pipeline from folder?

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