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8-9 DeepSeek-R1 Model

PANDORA DEVELOPER GUIDE · CHAPTER 08

Learning Objectives​

Use a Python program to download the DeepSeek-R1 model from the Hugging Face platform, and use simple prompts to ask DeepSeek-R1 questions and get answers.

8-9 DeepSeek-R1 Model

What is DeepSeek-R1?​

DeepSeek-R1 is a large language model developed by DeepSeek. It is like an AI model that can understand text, write articles, answer questions, and generate responses after thoughtful reasoning.

What Can DeepSeek-R1 Do?​

1. Provide automated customer service

2. Perform summarization or translation

3. Assist with programming

4. Analyze documents, contracts, and reports

How to Get Started?​

1. The following example code will make DeepSeek-R1 generate an answer to the prompt: "Please briefly explain the concept of quantum entanglement."

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
from transformers import pipeline
model_id = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained(
    model_id,
    trust_remote_code=True,  # Trust remote code execution
    cache_dir="./model",  # Specify model cache directory, default is ~/.cache/huggingface
)
# Load model
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    trust_remote_code=True,  # Trust remote code execution
    torch_dtype=torch.float16,  # Specify model data type (float16)
    device_map="auto",  # Automatically select device (CPU or GPU)
    cache_dir="./model",  # Specify model cache directory, default is ~/.cache/huggingface
)
# Create a text generation pipeline
generator = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    max_length=512,  # Maximum number of new tokens to generate
    temperature=0.6,  # Controls randomness of generation
    top_p=0.95,  # Only consider tokens with cumulative probability up to 0.95
    repetition_penalty=1.1,  # Penalty to reduce repeated content during generation
)
# Generate text and output
prompt = "Please briefly explain the concept of quantum entanglement."
outputs = generator(prompt, num_return_sequences=1)
print(outputs[0]["generated_text"])

2. After running it, you will see a response similar to the following:

8-9 DeepSeek-R1 Model

Reference:​

deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B · Hugging Face

Adapted from the original YUAN Developer Hub article. Source ID: 276.

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