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[SPARKNLP-1079] AutoGGUFVisionModel #14505
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Merged
maziyarpanahi
merged 16 commits into
JohnSnowLabs:release/600-release-candidate
from
DevinTDHa:feature/SPARKNLP-1079-AutoGGUFVisionModel
Mar 16, 2025
Merged
[SPARKNLP-1079] AutoGGUFVisionModel #14505
maziyarpanahi
merged 16 commits into
JohnSnowLabs:release/600-release-candidate
from
DevinTDHa:feature/SPARKNLP-1079-AutoGGUFVisionModel
Mar 16, 2025
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Description
This PR introduces the AutoGGUFVisionModel, enabling multimodal inference of llama.cpp GGUF models. The default pretrained model is llava_v1.5_7b_Q4_0_gguf_en.
Users can provide an image column and a text column with captions. The output will be a document column with the completions generated by the multimodal LLM.
Note that this annotator does not use the usual byte format provided by the Spark image reader (openCV compatible format). Instead, it requires raw image file bytes (e.g. from a jpg or png) which will then be decoded in the backend. For convenience, this is now implemented as a function of the
ImageAssembler
calledImageAssembler.loadImagesAsBytes
.For example:
Click to expand Example
A full end to end example of how to use this annotator is available at https://github.com/DevinTDHa/spark-nlp/blob/feature/SPARKNLP-1079-AutoGGUFVisionModel/examples/python/llama.cpp/llama.cpp_in_Spark_NLP_AutoGGUFVisionModel.ipynb
Motivation and Context
Enables users to caption images using multimodal LLMs.
How Has This Been Tested?
Tested the scala, python side locally, on databricks and colab.
Screenshots (if appropriate):
Types of changes
Checklist: