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Model: Kukedlc/Phi-3-Vision-Win-snap
Source: Original Platform

README.md

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+---
+license: mit
+license_link: https://huggingface.co/microsoft/Phi-3-vision-128k-instruct/resolve/main/LICENSE
+
+language:
+- multilingual
+pipeline_tag: text-generation
+tags:
+- nlp
+- code
+- vision
+inference:
+  parameters:
+    temperature: 0.7
+widget:
+  - messages:
+      - role: user
+        content: <|image_1|>Can you describe what you see in the image?
+---
+## Model Summary
+
+Phi-3 Vision is a lightweight, state-of-the-art open multimodal model built upon datasets which include - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data both on text and vision.  The model belongs to the Phi-3 model family, and the multimodal version comes with 128K context length (in tokens) it can support. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures.
+
+Resources and Technical Documentation:
+
++ [Phi-3 Microsoft Blog](https://aka.ms/Phi-3Build2024)
++ [Phi-3 Technical Report](https://aka.ms/phi3-tech-report)
++ [Phi-3 on Azure AI Studio](https://aka.ms/try-phi3vision)
++ [Phi-3 Cookbook](https://github.com/microsoft/Phi-3CookBook)
+
+
+```python
+from PIL import Image 
+import requests 
+from transformers import AutoModelForCausalLM 
+from transformers import AutoProcessor 
+
+model_id = "Kukedlc/Phi-3-Vision-Win-snap" 
+
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cuda", trust_remote_code=True, torch_dtype="auto")
+
+processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True) 
+
+messages = [ 
+    {"role": "user", "content": "<|image_1|>\nWhat is shown in this image?"}, 
+    {"role": "assistant", "content": "The chart displays the percentage of respondents who agree with various statements about their preparedness for meetings. It shows five categories: 'Having clear and pre-defined goals for meetings', 'Knowing where to find the information I need for a meeting', 'Understanding my exact role and responsibilities when I'm invited', 'Having tools to manage admin tasks like note-taking or summarization', and 'Having more focus time to sufficiently prepare for meetings'. Each category has an associated bar indicating the level of agreement, measured on a scale from 0% to 100%."}, 
+    {"role": "user", "content": "Provide insightful questions to spark discussion."} 
+] 
+
+url = "https://assets-c4akfrf5b4d3f4b7.z01.azurefd.net/assets/2024/04/BMDataViz_661fb89f3845e.png" 
+image = Image.open(requests.get(url, stream=True).raw) 
+
+prompt = processor.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+inputs = processor(prompt, [image], return_tensors="pt").to("cuda:0") 
+
+generation_args = { 
+    "max_new_tokens": 500, 
+    "temperature": 0.0, 
+    "do_sample": False, 
+} 
+
+generate_ids = model.generate(**inputs, eos_token_id=processor.tokenizer.eos_token_id, **generation_args) 
+
+# remove input tokens 
+generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
+response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] 
+
+print(response)
+```