emgena/omnimcp_mcp_github_issue_pr_ops_teaser

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🚀 Emgena AI Labs: GitHub MCP Operations & Automated PR Code Reviews (Evaluation Teaser Edition)

🔥 READY FOR PRODUCTION MULTI-TURN AGENT FINE-TUNING?

You are currently inspecting the Free Evaluation Teaser (10 multi-turn samples).

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Dataset Size	10 Samples (Preview)	30 - 100+ Enterprise Scenarios
Self-Healing & Retries	Basic (<20%)	>60% Real Error Injections & AST Repairs
Turnkey Fine-Tuning	Raw Parquet / JSON	1-Click Unsloth Google Colab Notebook & PyTorch Code
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Format Compatibility	Parquet only	Parquet + ShareGPT + Alpaca JSON + AST Schemas

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Every Emgena dataset is engineered as a precision-fit building block within a comprehensive enterprise AI hierarchy:

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⚡ 3-Line Python Quickstart (Loading Teaser Data)

from datasets import load_dataset

# Load the free evaluation teaser directly into Hugging Face Datasets
dataset = load_dataset("bacard/omnimcp_mcp_github_issue_pr_ops_teaser")

print(f"Total Teaser Rows: {len(dataset['train'])}")
print("First conversation turn:")
print(dataset["train"][0]["instruction"])