Update README.md

README.md

@@ -1,3 +1,82 @@
----
-license: mit
----
+---
+license: mit
+---
+
+# **Phi-3.5 Vision OpenVINO INT4 Model**
+
+This is the OpenVINO format INT 4 quantized version of the Microsoft Phi-3.5 VISIOn. You can use run this script to convert
+
+```python
+
+import requests
+from pathlib import Path
+
+if not Path("ov_phi3_vision.py").exists():
+    r = requests.get(url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/phi-3-vision/ov_phi3_vision.py")
+    open("ov_phi3_vision.py", "w").write(r.text)
+
+
+if not Path("gradio_helper.py").exists():
+    r = requests.get(url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/phi-3-vision/gradio_helper.py")
+    open("gradio_helper.py", "w").write(r.text)
+
+if not Path("notebook_utils.py").exists():
+    r = requests.get(url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py")
+    open("notebook_utils.py", "w").write(r.text)
+
+from ov_phi3_vision import convert_phi3_model
+
+from pathlib import Path
+import nncf
+
+
+model_id = "microsoft/Phi-3.5-vision-instruct"
+out_dir = Path("Save Your Phi-3.5-vision OpenVINO INT4 PATH")
+compression_configuration = {
+    "mode": nncf.CompressWeightsMode.INT4_SYM,
+    "group_size": 64,
+    "ratio": 0.6,
+}
+
+convert_phi3_model(model_id, out_dir, compression_configuration)
+
+```
+
+## **Sample Code**
+
+
+```python
+
+from ov_phi3_vision import OvPhi3Vision
+
+from notebook_utils import device_widget
+
+device = device_widget(default="GPU", exclude=["NPU"])
+
+out_dir = Path("Your Phi-3.5-vision OpenVINO INT4 PATH")
+
+model = OvPhi3Vision(out_dir, device.value)
+
+import requests
+from PIL import Image
+
+image = Image.open(r"Your local image Path")
+
+from transformers import AutoProcessor, TextStreamer
+
+messages = [
+    {"role": "user", "content": "<|image_1|>\nPlease analyze the image"},
+]
+
+processor = AutoProcessor.from_pretrained(out_dir, trust_remote_code=True)
+
+prompt = processor.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+inputs = processor(prompt, [image], return_tensors="pt")
+
+generation_args = {"max_new_tokens": 500, "do_sample": False, "streamer": TextStreamer(processor.tokenizer, skip_prompt=True, skip_special_tokens=True)}
+
+print("Analyze:")
+generate_ids = model.generate(**inputs, eos_token_id=processor.tokenizer.eos_token_id, **generation_args)
+
+```