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Soloman2002
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hermit-code-7b

Text Generation
Safetensors
Rust
English
qwen2
code
coding-agent
instruction-tuned
hermit-code
qwen2.5-coder
python
javascript
go
conversational
Model card Files
xet
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Hermit Code 7B

The official coding model for the Hermit AI Agent

Parameters Context License Format Python

📑 Table of Contents

🚀 Quick Start

Get up and running in 3 lines of code:

from transformers import pipeline

# Initialize the model
pipe = pipeline("text-generation", model="Soloman2002/hermit-code-7b")

# Start coding
chat = [{"role": "user", "content": "Write a Python function to reverse a linked list"}]
response = pipe(chat, max_new_tokens=512)

print(response[0]["generated_text"][-1]["content"])

💡 Tip: For best results, use temperature=0.2 and top_p=0.95 for deterministic code generation.

🎯 Capabilities

💻 Languages 🏗️ Code Gen 📖 Explain 🐛 Debug ⚡ Refactor 🧠 Context
Python Functions Breakdowns Bug Finding Performance 128K Tokens
JavaScript / TypeScript Classes Documentation Fixing Cleanup Multi-file
Go Scripts Architecture Optimization Restructuring Projects
Rust Full Projects Best Practices Analysis Modernization Understanding
C++
Java

✨ What Makes Hermit Code Special?

  • 🌐 Multi-Language Mastery — Native fluency in 6+ programming languages
  • 📦 Project-Scale Context — Understand entire codebases with 128K token context
  • 🔍 Debugging Expert — Identifies bugs, explains why they happen, and fixes them
  • 🎓 Educational — Explains complex concepts with clear, step-by-step reasoning
  • ⚙️ Production-Ready — Optimized for both research and deployment via vLLM

🧠 Model Details

Property Specification Notes
Base Model Qwen/Qwen2.5-Coder-7B-Instruct State-of-the-art code foundation
Architecture Qwen2.5 Dense Transformer Optimized for code understanding
Parameters 7.61B (6.53B non-embedding) Efficient size-to-performance ratio
Layers 28 Deep representation learning
Attention GQA — 28 Q heads, 4 KV heads Fast inference with grouped queries
Context Length 131,072 tokens ~100K+ lines of code context
License Apache 2.0 Commercial use permitted
Format Safetensors (BF16) Safe, efficient serialization

💻 Usage

Transformers

Perfect for prototyping and local development:

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# Load model and tokenizer
model_id = "Soloman2002/hermit-code-7b"
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_id)

# Prepare chat messages
messages = [
    {"role": "system", "content": "You are Hermit Code, an expert coding assistant."},
    {"role": "user", "content": "Write a Rust function that checks if a string is a palindrome."}
]

# Apply chat template
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

# Generate
inputs = tokenizer([text], return_tensors="pt").to(model.device)
outputs = model.generate(
    **inputs,
    max_new_tokens=512,
    temperature=0.2,
    do_sample=True
)

# Decode response
response = tokenizer.decode(
    outputs[0][inputs.input_ids.shape[1]:],
    skip_special_tokens=True
)
print(response)

vLLM (Recommended for Production)

For high-throughput serving and API deployment:

1. Install & Launch:

pip install vllm
vllm serve "Soloman2002/hermit-code-7b" --dtype bfloat16

2. Query via API:

curl -X POST "http://localhost:8000/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Soloman2002/hermit-code-7b",
    "messages": [
      {"role": "system", "content": "You are Hermit Code, a coding assistant."},
      {"role": "user", "content": "Explain closures in JavaScript with examples."}
    ],
    "temperature": 0.2,
    "max_tokens": 512
  }'

🚀 vLLM Benefits: Continuous batching, PagedAttention, and 10-20x throughput improvement over standard Transformers.

Inference API

Use Hugging Face's hosted infrastructure for instant access:

from huggingface_hub import InferenceClient

client = InferenceClient(token="hf_YOUR_TOKEN")

response = client.chat_completion(
    model="Soloman2002/hermit-code-7b",
    messages=[
        {"role": "user", "content": "Write a Go function to merge two sorted arrays"}
    ],
    max_tokens=512,
    temperature=0.2,
    stream=False
)

print(response.choices[0].message.content)

🎨 Interactive Examples

Click any language below to expand and see Hermit Code in action:

🐍 Python — Quick Sort Implementation 
def quick_sort(arr: list[int]) -> list[int]:
    """
    Sorts an array using the quicksort algorithm.
    Time Complexity: O(n log n) average, O(n²) worst case
    Space Complexity: O(log n) due to recursion
    """
    if len(arr) <= 1:
        return arr

    pivot = arr[len(arr) // 2]
    left = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right = [x for x in arr if x > pivot]

    return quick_sort(left) + middle + quick_sort(right)


# Example usage
if __name__ == "__main__":
    data = [3, 6, 8, 10, 1, 2, 1]
    print(f"Original: {data}")
    print(f"Sorted:   {quick_sort(data)}")

Key Features Demonstrated:

  • ✅ Type hints for better code clarity
  • ✅ Docstrings with complexity analysis
  • ✅ Recursive divide-and-conquer approach
  • ✅ Idiomatic Python list comprehensions
🦀 Rust — Palindrome Checker 
/// Checks if a string is a palindrome, ignoring non-alphanumeric characters
/// and case differences.
/// 
/// # Examples
/// ```
/// assert!(is_palindrome("A man, a plan, a canal: Panama"));
/// assert!(!is_palindrome("Hello, World!"));
/// ```
fn is_palindrome(s: &str) -> bool {
    let chars: Vec<char> = s
        .chars()
        .filter(|c| c.is_alphanumeric())
        .map(|c| c.to_ascii_lowercase())
        .collect();

    let len = chars.len();
    for i in 0..len / 2 {
        if chars[i] != chars[len - 1 - i] {
            return false;
        }
    }
    true
}

fn main() {
    let test_cases = vec![
        "racecar",
        "A man, a plan, a canal: Panama",
        "Hello, World!",
    ];

    for case in test_cases {
        println!("'{}' -> {}", case, is_palindrome(case));
    }
}

Key Features Demonstrated:

  • ✅ Memory-safe string processing
  • ✅ Functional iterator chains
  • ✅ Comprehensive documentation
  • ✅ Efficient two-pointer comparison
🐹 Go — Merge Sorted Arrays 
package main

import "fmt"

// mergeSorted combines two sorted integer slices into a single sorted slice.
// It runs in O(n + m) time where n and m are the lengths of the inputs.
func mergeSorted(a, b []int) []int {
    result := make([]int, 0, len(a)+len(b))
    i, j := 0, 0

    // Merge while both arrays have elements
    for i < len(a) && j < len(b) {
        if a[i] < b[j] {
            result = append(result, a[i])
            i++
        } else {
            result = append(result, b[j])
            j++
        }
    }

    // Append remaining elements
    result = append(result, a[i:]...)
    result = append(result, b[j:]...)

    return result
}

func main() {
    a := []int{1, 3, 5, 7}
    b := []int{2, 4, 6, 8}

    merged := mergeSorted(a, b)
    fmt.Printf("Merged: %v\n", merged) // [1 2 3 4 5 6 7 8]
}

Key Features Demonstrated:

  • ✅ Pre-allocated slices for zero-allocation growth
  • ✅ Two-pointer technique for optimal performance
  • ✅ Idiomatic Go error-free design
  • ✅ Clean, readable control flow
⚡ JavaScript — Closure Example 
/**
 * Creates a counter with private state using closures.
 * Demonstrates lexical scoping and data encapsulation.
 */
function createCounter(initialValue = 0) {
    let count = initialValue; // Private variable

    return {
        increment() {
            count += 1;
            return count;
        },
        decrement() {
            count -= 1;
            return count;
        },
        getValue() {
            return count;
        },
        reset() {
            count = initialValue;
            return count;
        }
    };
}

// Usage
const counter = createCounter(10);
console.log(counter.increment()); // 11
console.log(counter.increment()); // 12
console.log(counter.getValue());  // 12
console.log(counter.reset());     // 10

Key Features Demonstrated:

  • ✅ True private state via closures
  • ✅ Clean object interface
  • ✅ ES6 method shorthand syntax
  • ✅ Default parameter values

📊 Benchmarks

Benchmark Score Status Comparison to Base
HumanEval (Python) TBD 🔄 Pending vs Qwen2.5-Coder-7B
HumanEval (Multi-Lang) TBD 🔄 Pending vs Qwen2.5-Coder-7B
MBPP (Python) TBD 🔄 Pending vs Qwen2.5-Coder-7B
DS-1000 (Data Science) TBD 🔄 Pending vs Qwen2.5-Coder-7B

📈 Coming Soon: Comprehensive evaluation results based on the Qwen2.5-Coder-7B-Instruct baseline with additional fine-tuning for agentic coding workflows.

🤝 Acknowledgments

Contribution Team / Resource Link
🏗️ Base Model Qwen Team Qwen2.5-Coder-7B-Instruct
🤖 Hermit AI Agent Hermit Team GitHub: Soloman2002
📦 Infrastructure Hugging Face Transformers & vLLM

🌟 Star Us on GitHub!

If you find Hermit Code useful, please consider starring the repository and sharing with your network.

Star on GitHub Follow on Hugging Face

Built with ❤️ for the coding community by the Hermit Team

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