README.md

---
library_name: transformers
license: mit
language:
- th
pipeline_tag: image-to-text
base_model: Salesforce/blip2-opt-2.7b-coco
---

## THAI-BLIP-2
 fine-tuned for image captioning task from [blip2-opt-2.7b-coco](Salesforce/blip2-opt-2.7b-coco) with MSCOCO2017 thai caption.

## How to use:
  ```python
  from transformers import Blip2ForConditionalGeneration, Blip2Processor
  from PIL import Image
  import torch
  
  device = "cuda" if torch.cuda.is_available() else "cpu"
  
  processor = Blip2Processor.from_pretrained("kkatiz/THAI-BLIP-2")
  model = Blip2ForConditionalGeneration.from_pretrained("kkatiz/THAI-BLIP-2", device_map=device, torch_dtype=torch.bfloat16)

  img = Image.open("Your image...")
  inputs = processor(images=img, return_tensors="pt").to(device, torch.bfloat16)

  # Adjust your `max_length`
  generated_ids = model.generate(**inputs, max_length=20)
  generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)
  print(generated_text)
  ```