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Hello! I was finetuning from the pretrained_flant5xl and pretrained_opt2.7b models, much to my surprise the flant5xl model is excelling at creating correct labels, as my captions are actually a string…
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### Describe your use-case.
request:
Anyway with my issues dyslexic and spelling, i have a txt document with key words to my styles etc I always use,
I copy and past the text into every txt made…
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Hello author, is this a fine-tuning project for BLIP2 on an image captioning dataset?
I am searching everywhere for fine-tuning projects for BLIP2 in image captions, and I hope you can bring me good …
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a) In the `forward` function of `class LSTMModel` the parameter `capts` is used, but
the `self.embedding_layer` gets `caps` without the character **t**
```
def forward(self, input_features, capt…
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Hi there,
I am aware that Virtex used image captioning as a pretraining task and not as the "final goal", but I was wondering whether one could go on fine-tuning the pretrained model (e.g. bicaptioni…
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Hi @pinakinathc ,
Thanks for the implementation of the excellent work. I have a few questions about your code implementations. It would be really kind of you if you could answer them:
(1) As is …
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I got the following error trying to preprocess images with the train tab:
Error completing request
Arguments: ('/content/gdrive/MyDrive/AI Training/HiT/Trained HT (Retagged)/Retagged', '/content/g…
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Hi,It's a nice work and very helpful for beginners.
there is a issue when I write my own code according to your code in image captioning model.
in the example of training phase,you said that for a i…
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> Traditional OCR datasets can be transformed into instruction-following datasets. For example, in the traditional OCR dataset, a data sample is an image with OCR ground truths.
>
> W…
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- https://arxiv.org/abs/2106.09436
- 2021
現在の最先端の画像キャプションモデルは、自己回帰型デコーダを採用しており、過去に生成された単語を条件として各単語を生成するため、推論時の遅延が大きくなります。
この問題を解決するために,すべての単語を並列に生成することで推論速度を大幅に向上させる非自動回帰型画像キャプションモデルが最近提案されている.
…
e4exp updated
3 years ago