Update README.md

README.md

@@ -13,3 +13,108 @@ tags:
 - flux
 ---
 ![9.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/esgwb8sdL5LbyDuQFLWnT.png)
+# **JSONify-Flux-Large**
+
+The **JSONify-Flux-Large** model is a fine-tuned version of **Qwen2VL**, specifically trained on **Flux-generated images** and their **corresponding captions**. This model has been trained using a **30M trainable parameter** dataset and is designed to output responses in structured **JSON format** while maintaining state-of-the-art performance in **Optical Character Recognition (OCR)**, **image-to-text conversion**, and **math problem-solving with LaTeX formatting**.
+
+### Key Enhancements:
+
+* **Optimized for Flux-Generated Image Captioning**: JSONify-Flux-Large has been trained to understand and describe images created using Flux-based generation techniques.
+
+* **State-of-the-Art Image Understanding**: Built on Qwen2VL's architecture, JSONify-Flux-Large excels in visual reasoning tasks like DocVQA, RealWorldQA, MTVQA, and more.
+
+* **Formatted JSON Output**: Responses are structured in a JSON format, making it ideal for automation, database storage, and further processing.
+
+* **Multilingual Support**: Recognizes and extracts text from images in multiple languages, including English, Chinese, Japanese, Arabic, and various European languages.
+
+* **Supports Multi-Turn Interactions**: Maintains context in conversations and can provide extended reasoning over multiple inputs.
+
+### How to Use
+
+```python
+from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor
+from qwen_vl_utils import process_vision_info
+
+# Load the model on the available device(s)
+model = Qwen2VLForConditionalGeneration.from_pretrained(
+    "prithivMLmods/JSONify-Flux-Large", torch_dtype="auto", device_map="auto"
+)
+
+# Enable flash_attention_2 for better acceleration and memory efficiency
+# model = Qwen2VLForConditionalGeneration.from_pretrained(
+#     "prithivMLmods/JSONify-Flux-Large",
+#     torch_dtype=torch.bfloat16,
+#     attn_implementation="flash_attention_2",
+#     device_map="auto",
+# )
+
+# Default processor
+processor = AutoProcessor.from_pretrained("prithivMLmods/JSONify-Flux-Large")
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "image",
+                "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
+            },
+            {"type": "text", "text": "Describe this image in JSON format."},
+        ],
+    }
+]
+
+# Prepare inputs for inference
+text = processor.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True
+)
+image_inputs, video_inputs = process_vision_info(messages)
+inputs = processor(
+    text=[text],
+    images=image_inputs,
+    videos=video_inputs,
+    padding=True,
+    return_tensors="pt",
+)
+inputs = inputs.to("cuda")
+
+# Inference: Generate JSON-formatted output
+generated_ids = model.generate(**inputs, max_new_tokens=128)
+generated_ids_trimmed = [
+    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
+]
+output_text = processor.batch_decode(
+    generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+)
+
+print(output_text)  # JSON-formatted response
+```
+
+### JSON Buffer Handling
+```python
+buffer = ""
+for new_text in streamer:
+    buffer += new_text
+    buffer = buffer.replace("<|im_end|>", "")
+    yield buffer
+```
+
+### **Key Features**
+
+1. **Flux-Based Vision-Language Model**:
+   - Specifically trained on **Flux-generated images and captions** for precise image-to-text conversion.
+
+2. **Optical Character Recognition (OCR)**:
+   - Extracts and processes text from images with high accuracy.
+
+3. **Math and LaTeX Support**:
+   - Solves math problems and outputs equations in **LaTeX format**.
+
+4. **Structured JSON Output**:
+   - Ensures outputs are formatted in JSON, making it suitable for API responses and automation tasks.
+
+5. **Multi-Image and Video Understanding**:
+   - Supports analyzing multiple images and video content up to **20 minutes long**.
+
+6. **Secure Weight Format**:
+   - Uses **Safetensors** for enhanced security and faster model loading.