To use DeepSeek in offline mode, follow these steps:

1. Download the DeepSeek Model

• Visit the official DeepSeek website or repository (e.g., GitHub) to download the model files.
• Ensure you have the necessary dependencies and libraries installed on your system.

2. Set Up the Environment

• Install Python and required libraries (e.g., PyTorch, TensorFlow, or ONNX, depending on the model format).
• Use a virtual environment to manage dependencies:

bash

python -m venv deepseek-env
source deepseek-env/bin/activate # On Windows: deepseek-env\Scripts\activate
pip install -r requirements.txt # Install dependencies from the provided file

3. Load the Model Offline

• Place the downloaded model files in your project directory.
• Load the model in your Python script:

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = “path_to_downloaded_model”
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path)

Example usage

input_text = “How does DeepSeek work?”
inputs = tokenizer(input_text, return_tensors=”pt”)
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

4. Run the Model

• Execute your script to use the model offline:

bash

python your_script.py

5. Optimize for Offline Use

• Ensure your system meets the hardware requirements (e.g., GPU for faster inference).
• Use quantization or smaller model variants if resources are limited.

6. Test and Validate

• Verify the model’s functionality by testing it with various inputs.
• Adjust parameters or fine-tune the model if necessary.

Notes:

• Offline mode requires all necessary files (e.g., tokenizers, configs) to be downloaded and accessible locally.
• Check the DeepSeek documentation for specific instructions or updates.