> ## Documentation Index
> Fetch the complete documentation index at: https://docs.exla.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# DeepSeek R1

> A powerful large language model for text generation and reasoning optimized for any device

# DeepSeek R1 Model

DeepSeek R1 is a powerful large language model (LLM) designed for text generation, reasoning, and code generation tasks. With InferX, you can run DeepSeek R1 on any device using the same API - from edge devices to powerful servers.

## Features

* **Advanced Reasoning**: State-of-the-art reasoning and problem-solving capabilities
* **Code Generation**: Expert-level code generation and explanation
* **Cross-Platform**: Same code works on Jetson, GPU, or CPU
* **Hardware-Optimized**: Automatically detects and optimizes for your hardware
* **Real-time Processing**: Optimized for fast inference across all platforms

## Installation

DeepSeek R1 is included with InferX:

```bash theme={null}
pip install git+https://github.com/exla-ai/InferX.git
```

## Basic Usage

```python theme={null}
from inferx.models.deepseek_r1 import deepseek_r1

# Initialize the model (automatically detects your hardware)
model = deepseek_r1()

# Run the interactive interface
model.run()
```

## Advanced Usage

### Text Generation

```python theme={null}
# Generate text with custom parameters
response = model.generate(
    prompt="Write a short poem about artificial intelligence.",
    max_tokens=100,
    temperature=0.7,
    top_p=0.9,
    top_k=40
)

print(response)
```

### Code Generation

```python theme={null}
# Generate and explain code
code_response = model.generate(
    prompt="Write a Python function to calculate the Fibonacci sequence",
    max_tokens=200,
    temperature=0.3  # Lower temperature for more deterministic code
)

print(code_response)
```

### System Prompts

```python theme={null}
# Use system prompts to guide behavior
response = model.generate(
    prompt="What is machine learning?",
    system_prompt="You are a helpful AI assistant that explains complex topics in simple terms.",
    max_tokens=150
)

print(response)
```

## Parameters

| Parameter     | Description                                | Default | Range   |
| ------------- | ------------------------------------------ | ------- | ------- |
| `max_tokens`  | Maximum number of tokens to generate       | 256     | 1-2048  |
| `temperature` | Controls randomness (higher = more random) | 0.8     | 0.0-2.0 |
| `top_p`       | Nucleus sampling parameter                 | 0.95    | 0.0-1.0 |
| `top_k`       | Limits vocabulary to top k tokens          | 40      | 1-100   |

## Performance

InferX optimizes DeepSeek R1 for your hardware:

| Hardware        | Tokens/Second | Memory Usage |
| --------------- | ------------- | ------------ |
| Jetson AGX Orin | \~15          | \~8GB        |
| RTX 4090        | \~50          | \~12GB       |
| Intel i7 CPU    | \~5           | \~6GB        |

## Example Applications

### Chatbot Development

```python theme={null}
def create_chatbot():
    model = deepseek_r1()
    
    print("DeepSeek R1 Chatbot (type 'exit' to quit)")
    
    while True:
        user_input = input("You: ")
        if user_input.lower() == 'exit':
            break
            
        response = model.generate(
            prompt=user_input,
            system_prompt="You are a helpful assistant.",
            max_tokens=200
        )
        
        print(f"Assistant: {response}")

# Run the chatbot
create_chatbot()
```

### Code Assistant

```python theme={null}
def code_assistant():
    model = deepseek_r1()
    
    system_prompt = """You are an expert programmer. Provide clear, 
    well-commented code solutions and explanations."""
    
    while True:
        question = input("Code question: ")
        if question.lower() == 'exit':
            break
            
        response = model.generate(
            prompt=question,
            system_prompt=system_prompt,
            temperature=0.3,  # More deterministic for code
            max_tokens=300
        )
        
        print(f"Solution:\n{response}\n")

code_assistant()
```

## Hardware Detection

```
✨ InferX - DeepSeek R1 Model ✨
🔍 Device Detected: AGX_ORIN
⠏ [2.5s] Loading DeepSeek R1 model
✓ [3.0s] Ready for text generation
```

## Next Steps

* Try [CLIP model](/models/clip) for multimodal understanding
* Explore [practical examples](https://github.com/exla-ai/InferX-examples/tree/main/deepseek_r1)
* Learn about [custom model optimization](/models/custom-models/overview)