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Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>
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Jael Gu 2 months ago
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      README.md

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README.md

@ -69,6 +69,8 @@ An image captioning operator takes a [towhee image](link/to/towhee/image/api/doc
​ The caption generated by model.
# More Resources
- [What is a Transformer Model? An Engineer's Guide](https://zilliz.com/glossary/transformer-models): A transformer model is a neural network architecture. It's proficient in converting a particular type of input into a distinct output. Its core strength lies in its ability to handle inputs and outputs of different sequence length. It does this through encoding the input into a matrix with predefined dimensions and then combining that with another attention matrix to decode. This transformation unfolds through a sequence of collaborative layers, which deconstruct words into their corresponding numerical representations.
@ -83,4 +85,3 @@ At its heart, a transformer model is a bridge between disparate linguistic struc
- [What is a Generative Adversarial Network? An Easy Guide](https://zilliz.com/glossary/generative-adversarial-networks): Just like we classify animal fossils into domains, kingdoms, and phyla, we classify AI networks, too. At the highest level, we classify AI networks as "discriminative" and "generative." A generative neural network is an AI that creates something new. This differs from a discriminative network, which classifies something that already exists into particular buckets. Kind of like we're doing right now, by bucketing generative adversarial networks (GANs) into appropriate classifications.
So, if you were in a situation where you wanted to use textual tags to create a new visual image, like with Midjourney, you'd use a generative network. However, if you had a giant pile of data that you needed to classify and tag, you'd use a discriminative model.
- [Zilliz partnership with PyTorch - View image search solution tutorial](https://zilliz.com/partners/pytorch): Zilliz partnership with PyTorch
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