Update README.md

README.md

@@ -1,3 +1,71 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- Fancy-MLLM/R1-OneVision
+base_model:
+- Qwen/Qwen2.5-VL-7B-Instruct
+pipeline_tag: image-text-to-text
+---
+
+## Model Overview
+
+This is a multimodal large language model fine-tuned from Qwen2.5-VL on the **R1-OneVision** dataset. The model enhances vision-language understanding and reasoning capabilities, making it suitable for various tasks such as visual reasoning, image understanding.
+
+## Performance
+
+| Task               | Metric  | Score |
+|--------------------|---------|-------|
+| Image Captioning  | BLEU-4  | XX.XX |
+| VQA               | Accuracy | XX.XX |
+| Scene Understanding | mAP    | XX.XX |
+
+## Usage
+
+You can load the model using the Hugging Face `transformers` library:
+
+```python
+from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
+from qwen_vl_utils import process_vision_info
+
+model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
+    "Fancy-MLLM/R1-OneVison/R1-OneVison-7B", torch_dtype="auto", device_map="auto"
+)
+
+processor = AutoProcessor.from_pretrained("Fancy-MLLM/R1-OneVison/R1-OneVison-7B")
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image", "image": "<your image path>"},
+            {"type": "text", "text": "Hint: Please answer the question and provide the final answer at the end. Question: Which number do you have to write in the last daisy?"},
+        ],
+    }
+]
+
+# Preparation 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(model.device)
+
+generated_ids = model.generate(**inputs, max_new_tokens=4096)
+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)
+```
+## Model Contact
+Xiaoxuan He: [email protected]
+Hongkun Pan: [email protected]