README.md

metadata

license: apache-2.0
base_model: openai/gpt-oss-20b
tags:
  - merge-conflicts
  - git-automation
  - developer-tools
  - code-generation
  - version-control
  - devops
languages:
  - en
pipeline_tag: text-generation
library_name: transformers
datasets:
  - SoarAILabs/merge-conflict-dataset
metrics:
  - name: exact_match
    type: exact_match
    value: 22
  - name: token_f1
    type: f1
    value: 0.617
  - name: bleu
    type: bleu
    value: 50.82
  - name: rouge-l
    type: rouge
    value: 58.64
  - name: levenshtein_sim
    type: similarity
    value: 0.549
  - name: char_similarity
    type: similarity
    value: 0.765
model-index:
  - name: KiteResolve-20B
    results:
      - task:
          type: text-generation
          name: Merge Conflict Resolution
        metrics:
          - name: Exact Match
            type: exact_match
            value: 22
          - name: Token F1
            type: f1
            value: 0.617
          - name: BLEU
            type: bleu
            value: 50.82
          - name: ROUGE-L
            type: rouge
            value: 58.64
          - name: Levenshtein Similarity
            type: similarity
            value: 0.549
          - name: Character Similarity
            type: similarity
            value: 0.765

🪁 KiteResolve-20B: AI-Powered Merge Conflict Resolution

Developed by Soar AI Labs

🚀 Model Description

KiteResolve-20B is a fine-tuned version of GPT-OSS-20B specifically engineered for automated Git merge conflict resolution. This model transforms the tedious process of manually resolving merge conflicts into an intelligent, automated workflow that understands code semantics across multiple programming languages.

✨ Key Features

• 🎯 20% Exact Match Accuracy on real-world merge conflicts
• 📈 12% Token-F1 Score Improvement over base model
• 🌐 Multi-Language Support: Java, JavaScript, Python, C#, TypeScript, and more
• ⚡ Fast Inference: Optimized for CLI and webhook integrations
• 🔧 Production Ready: Designed for enterprise Git workflows

📊 Performance Metrics

Model	Exact Match	Token F1	BLEU	ROUGE-L	Char Sim
codellama:13b	0.00	0.193	13.28	0.208	0.710
llama3.1:8b	0.04	0.583	50.59	0.610	0.818
gpt-oss:20b	0.24	0.549	47.19	0.572	0.736
KiteResolve-20B	0.22	0.617	50.82	0.586	0.765

Evaluated on 50 held-out samples from real-world merge conflicts.

🛠️ Usage

Quick Start

from transformers import AutoModelForCausalLM, AutoTokenizer
from unsloth.chat_templates import get_chat_template

# Load the model
model = AutoModelForCausalLM.from_pretrained("SoarAILabs/KiteResolve-20B")
tokenizer = AutoTokenizer.from_pretrained("SoarAILabs/KiteResolve-20B")
tokenizer = get_chat_template(tokenizer, chat_template="gpt-oss")

# Resolve a merge conflict
conflict = """
<<<<<<< ours
function calculateTotal(items) {
    return items.reduce((sum, item) => sum + item.price, 0);
}
=======
function calculateTotal(items) {
    return items.map(item => item.price).reduce((a, b) => a + b, 0);
}
>>>>>>> theirs
"""

messages = [{"role": "user", "content": f"Resolve this merge conflict:\n```{conflict}```"}]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)

inputs = tokenizer([prompt], return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=200, do_sample=False)

resolution = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(resolution)

Ollama 🦙️

ollama run hf.co/SoarAILabs/KiteResolve-20B/model-q4_k_m.gguf