Update README.md

README.md

@@ -5,5 +5,96 @@ datasets:
 language:
 - en
 base_model:
-- Qwen/Qwen2-VL-2B-Instruct
----
+- Qwen/Qwen2-VL-7B-Instruct
+---
+
+
+# lmms-lab/Qwen2-VL-7B-GRPO-8k
+
+## Model Summary
+
+This model is 7B parameter models trained on 8k curated [dataset](https://huggingface.co/datasets/lmms-lab/multimodal-open-r1-8k-verified) with GRPO
+
+- **Repository:** [EvolvingLMMs-Lab/open-r1-multimodal](https://github.com/EvolvingLMMs-Lab/open-r1-multimodal)
+- **Languages:** English, Chinese
+
+
+### Generation
+
+The generation of this model is the same as the original `Qwen/Qwen2-VL-7B-Instruct` simply changes the model_id in from pretrained would works
+
+```python
+from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor
+from qwen_vl_utils import process_vision_info
+
+SYSTEM_PROMPT = (
+    "A conversation between User and Assistant. The user asks a question, and the Assistant solves it. The assistant "
+    "first thinks about the reasoning process in the mind and then provides the user with the answer. The reasoning "
+    "process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively, i.e., "
+    "<think> reasoning process here </think><answer> answer here </answer>"
+)
+
+# default: Load the model on the available device(s)
+model = Qwen2VLForConditionalGeneration.from_pretrained(
+    "Qwen/Qwen2-VL-7B-Instruct", torch_dtype="auto", device_map="auto"
+)
+
+# default processer
+processor = AutoProcessor.from_pretrained("lmms-lab/Qwen2-VL-7B-GRPO-8k")
+
+# The default range for the number of visual tokens per image in the model is 4-16384. You can set min_pixels and max_pixels according to your needs, such as a token count range of 256-1280, to balance speed and memory usage.
+# min_pixels = 256*28*28
+# max_pixels = 1280*28*28
+# processor = AutoProcessor.from_pretrained("lmms-lab/Qwen2-VL-7B-GRPO-8k", min_pixels=min_pixels, max_pixels=max_pixels)
+
+messages = [
+    {"role": "system", "content": SYSTEM_PROMPT},
+    {
+        "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."},
+        ],
+    }
+]
+
+# 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("cuda")
+
+# Inference: Generation of the 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)
+
+
+```
+
+
+# Training
+
+## Model
+
+- **Architecture:** Qwen/Qwen2-VL-7B-Instruct
+- **Initialized Model:** Qwen/Qwen2-VL-7B-Instruct
+- **Data:** lmms-lab/multimodal-open-r1-8k-verified
+- **Precision:** bfloat16
+