Update README.md

README.md

@@ -1,3 +1,46 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- vi
+- en
+pipeline_tag: image-text-to-text
+library_name: transformers
+tags:
+- got
+- vision-language
+- ocr2.0
+- got_vietnamese
+---
+## Usage
+Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.10：
+```
+torch==2.0.1
+torchvision==0.15.2
+transformers==4.37.2
+tiktoken==0.6.0
+verovio==4.3.1
+accelerate==0.28.0
+```
+```python
+from transformers import AutoModel, AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained('tadkt/GOT_Vietnamese', trust_remote_code=True)
+model = AutoModel.from_pretrained('tadkt/GOT_Vietnamese', trust_remote_code=True, low_cpu_mem_usage=True, device_map='cuda', use_safetensors=True, pad_token_id=tokenizer.eos_token_id)
+model = model.eval().cuda()
+# input your test image
+image_file = 'xxx.jpg'
+# plain texts OCR
+res = model.chat(tokenizer, image_file, ocr_type='ocr')
+# format texts OCR:
+# res = model.chat(tokenizer, image_file, ocr_type='format')
+# fine-grained OCR:
+# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_box='')
+# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_box='')
+# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_color='')
+# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_color='')
+# multi-crop OCR:
+# res = model.chat_crop(tokenizer, image_file, ocr_type='ocr')
+# res = model.chat_crop(tokenizer, image_file, ocr_type='format')
+# render the formatted OCR results:
+# res = model.chat(tokenizer, image_file, ocr_type='format', render=True, save_render_file = './demo.html')
+print(res)
+```