Create README.md

README.md

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+---
+datasets:
+- AnyaSchen/image2poetry_ru
+language:
+- ru
+tags:
+- Esenin
+- image2poetry
+---
+
+This repo contains model for generation poetry in style of Esenin from image.
+
+To use this model you can do:
+
+```
+from PIL import Image
+import requests
+from transformers import AutoTokenizer, VisionEncoderDecoderModel, ViTImageProcessor
+
+def generate_poetry(fine_tuned_model, image, tokenizer):
+    pixel_values = feature_extractor(images=image, return_tensors="pt").pixel_values
+    pixel_values = pixel_values.to(device)
+
+    # Generate the poetry with the fine-tuned VisionEncoderDecoder model
+    generated_tokens = fine_tuned_model.generate(
+        pixel_values,
+        max_length=300,
+        num_beams=3,
+        top_p=0.8,
+        temperature=2.0,
+        do_sample=True,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id,
+    )
+
+    # Decode the generated tokens
+    generated_poetry = tokenizer.decode(generated_tokens[0], skip_special_tokens=True)
+    return generated_poetry
+
+path = 'AnyaSchen/vit-rugpt3-medium-esenin'
+fine_tuned_model = VisionEncoderDecoderModel.from_pretrained(path).to(device)
+feature_extractor = ViTImageProcessor.from_pretrained(path)
+tokenizer = AutoTokenizer.from_pretrained(path)
+
+url = 'https://anandaindia.org/wp-content/uploads/2018/12/happy-man.jpg'
+image = Image.open(requests.get(url, stream=True).raw)
+
+generated_poetry = generate_poetry(fine_tuned_model, image, tokenizer)
+print(generated_poetry)
+```