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--- |
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license: cc-by-4.0 |
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datasets: |
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- patomp/thai-mscoco-2014-captions |
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metrics: |
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- recall |
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--- |
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## Requirements |
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```bash |
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pip install pythainlp |
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pip install gensim>=4.3.1 |
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pip install git+https://github.com/openai/CLIP.git |
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``` |
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## Usage |
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Encode a text by |
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```python |
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from transformers import AutoModel |
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text = 'หมากำลังวิ่งในสนามหญ้า' |
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model = AutoModel.from_pretrained("patomp/thai-light-multimodal-clip-and-distill", trust_remote_code=True) |
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embeddings = model(text) |
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print("Text features shape:", embeddings.shape) |
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``` |
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Encode an image by |
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```python |
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import torch |
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import clip |
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import requests |
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from PIL import Image |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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model, preprocess = clip.load("ViT-B/32", device=device) |
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url = "http://images.cocodataset.org/val2017/000000039769.jpg" |
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image = Image.open(requests.get(url, stream=True).raw) |
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image = preprocess(image).unsqueeze(0).to(device) |
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with torch.no_grad(): |
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image_features = model.encode_image(image) |
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print("Image features shape:", image_features.shape) |
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``` |
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## Benchmark |
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On the test set of [Thai MS COCO 2014 dataset](https://huggingface.co/datasets/patomp/thai-mscoco-2014-captions) |
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| Model \ Metrics | text-find-image recall@1 | text-find-image recall@10 | image-find-text recall@1 | image-find-text recall@10 | # text samples per second* | |
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| :--- | --- | --- | --- | --- | --- | |
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| **Multilingual Encoder** | | | | | | |
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| [clip-ViT-B-32-multilingual-v1](https://huggingface.co/sentence-transformers/clip-ViT-B-32-multilingual-v1) | 0.075 | 0.242 | 0.096 | 0.286 | 251 | |
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| [XLM-Roberta-Large-Vit-B-32](https://huggingface.co/M-CLIP/XLM-Roberta-Large-Vit-B-32) | **0.226** | **0.565** | **0.265** | **0.596** | 20 | |
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| **Thai Encoder (WangchanBERTa-based)** | | | | | | |
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| [Thai-Cross-CLIP](https://github.com/vikimark/Thai-Cross-CLIP) | 0.167 | 0.475 | 0.197 | 0.523 | 48 | |
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| **Thai Encoder (Thai2Fit-based)** | | | | | | |
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| [thai-light-multimodal-clip-and-distill](https://huggingface.co/patomp/thai-light-multimodal-clip-and-distill) | 0.082 | **0.328** | 0.118 |**0.401**| 450 | |
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| [thai-light-multimodal-distill](https://huggingface.co/patomp/thai-light-multimodal-distill) | **0.084** | 0.319 | **0.122** |**0.401**| 450 | |
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## Reference |
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Some part of this content referenced from https://huggingface.co/M-CLIP/XLM-Roberta-Large-Vit-B-32. |
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For more detail, please visit https://github.com/calzonelover/Lightweight-Multi-modal-Encoder-for-Thai. |