Added info to readme

README.md

@@ -1,5 +1,32 @@
+---
+language:
+- th
+---
 # Thai Image Captioning
-A
+Encoder-decoder style image captioning model using [Swin-L](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) and [Wangchanberta](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased). Trained on Thai language MSCOCO and IPU24 dataset.
+
+# Usage
+
+With `VisionEncoderDecoderModel`.
+```
+from transformers import VisionEncoderDecoderModel, AutoImageProcessor, AutoTokenizer
+device = 'cuda'
+gen_kwargs = {"max_length": 120, "num_beams": 4}
+model_path = 'Natthaphon/thaicapgen-swin-wangchan'
+feature_extractor = AutoImageProcessor.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = VisionEncoderDecoderModel.from_pretrained(model_path).to(device)
+pixel_values = feature_extractor(images=[Image.open('/home/palm/Pictures/KDEScreenshot/Screenshot_20241030_110135.png')], return_tensors="pt").pixel_values
+pixel_values = pixel_values.to(device)
+output_ids = model.generate(pixel_values, **gen_kwargs)
+preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
+```
+You can also use `AutoModel` to load it. But this requires `trust_remote_code=True`.
+```
+from transformers import AutoModel
+model_path = 'Natthaphon/thaicapgen-swin-wangchan'
+model = AutoModel.from_pretrained(model_path, trust_remote_code=True).to(device)
+```
 
 # Acknowledgement
 This work is partially supported by the Program Management Unit for Human Resources & Institutional Development, Research and Innovation (PMU-B) [Grant number B04G640107]