Datasets:

ucsahin
/

Turkish-VLM-Mix-Benchmark

Tasks:

Image Feature Extraction

Image Classification

Modalities:

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Languages:

Size:

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ucsahin commited on Aug 9, 2024

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@@ -54,7 +54,7 @@ size_categories:
 - 10K<n<100K
 ---
-This is a Turkish multimodal (image-text-text triplets) datasets consisting of Turkish translated samples from the datasets [google/docci](https://huggingface.co/datasets/google/docci), [tomg-group-umd/pixelprose](https://huggingface.co/datasets/tomg-group-umd/pixelprose), [detection-datasets/coco](https://huggingface.co/datasets/detection-datasets/coco), [rafaelpadilla/coco2017](https://huggingface.co/datasets/rafaelpadilla/coco2017), [liuhaotian/LLaVA-Instruct-150K](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K), [liuhaotian/LLaVA-CC3M-Pretrain-595K](https://huggingface.co/datasets/liuhaotian/LLaVA-CC3M-Pretrain-595K), and [HuggingFaceM4/FairFace](https://huggingface.co/datasets/HuggingFaceM4/FairFace).
 The labels are in Turkish and the dataset is in an instruction-tuning format with separate columns for prompts and completion labels.
 The original labels (except liuhaotian/LLaVA-Instruct-150K) are translated using [google/gemma-2-9b-it](https://huggingface.co/CohereForAI/gemma-2-9b-it).
 For liuhaotian/LLaVA-Instruct-150K, a much more powerful [google/gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it) is used to construct question-answer pairs.

 - 10K<n<100K
 ---
+This is a Turkish multimodal (image-text-text triplets) dataset consisting of Turkish translated samples from the datasets [google/docci](https://huggingface.co/datasets/google/docci), [tomg-group-umd/pixelprose](https://huggingface.co/datasets/tomg-group-umd/pixelprose), [detection-datasets/coco](https://huggingface.co/datasets/detection-datasets/coco), [rafaelpadilla/coco2017](https://huggingface.co/datasets/rafaelpadilla/coco2017), [liuhaotian/LLaVA-Instruct-150K](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K), [liuhaotian/LLaVA-CC3M-Pretrain-595K](https://huggingface.co/datasets/liuhaotian/LLaVA-CC3M-Pretrain-595K), and [HuggingFaceM4/FairFace](https://huggingface.co/datasets/HuggingFaceM4/FairFace).
 The labels are in Turkish and the dataset is in an instruction-tuning format with separate columns for prompts and completion labels.
 The original labels (except liuhaotian/LLaVA-Instruct-150K) are translated using [google/gemma-2-9b-it](https://huggingface.co/CohereForAI/gemma-2-9b-it).
 For liuhaotian/LLaVA-Instruct-150K, a much more powerful [google/gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it) is used to construct question-answer pairs.