DeepSeek sample code for image processing

Setting Up DeepSeek Coder

1. Install Dependencies:
Ensure you have the necessary libraries installed. Run the following command in your terminal:

bash
   pip install -r requirements.txt
   

2. Import Required Libraries:
You will need to import the necessary libraries from the `transformers` package and any additional libraries for image processing, such as `PIL` for handling images.

3. Sample Code for Image Processing:
Here’s a basic example of how to load an image, process it using a model from DeepSeek, and display the result:

python
   from transformers import AutoTokenizer, AutoModelForImageClassification
   from PIL import Image
   import torch

   # Load the tokenizer and model
   tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base")
   model = AutoModelForImageClassification.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base").cuda()

   # Load and preprocess the image
   image = Image.open("path_to_your_image.jpg")
   inputs = tokenizer(image, return_tensors="pt").to(model.device)

   # Perform inference
   with torch.no_grad():
       outputs = model(**inputs)

   # Process the output (e.g., get predicted class)
   predictions = torch.argmax(outputs.logits, dim=-1)
   print(f"Predicted class: {predictions.item()}")
   

4. Explanation of Code:
- The code starts by importing necessary libraries.
- It loads a pre-trained model and tokenizer from DeepSeek.
- An image is opened using `PIL`, and then it is tokenized into a format suitable for the model.
- The model performs inference on the processed image.
- Finally, it retrieves and prints the predicted class of the image.

5. Running the Code:
Ensure that you replace `"path_to_your_image.jpg"` with the actual path to your image file. You can run this script in your Python environment after setting up DeepSeek.

By following these steps, you can effectively utilize DeepSeek for various image processing tasks. For more advanced functionalities or specific tasks, refer to additional documentation or examples provided in the DeepSeek GitHub repository [1].

Citations:
[1] https://github.com/deepseek-ai/deepseek-coder/?tab=readme-ov-file
[2] https://www.youtube.com/watch?v=qbUELF9Et4s
[3] https://www.datacamp.com/tutorial/deepseek-r1-project
[4] https://github.com/deepseek-ai/DeepSeek-R1/activity
[5] https://www.datacamp.com/tutorial/deepseek-v3
[6] https://dev.to/proflead/deepseek-ai-ai-that-crushed-openai-how-to-use-deepseek-r1-privately-22fl
[7] https://www.deepseek.com