neopolita/TexasHoldEm-Llama-3.2-1B-Instruct
TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Jan 17, 2026License:llama3.2Architecture:Transformer0.0K Warm
The neopolita/TexasHoldEm-Llama-3.2-1B-Instruct is a 1 billion parameter Llama 3.2 Instruct model, fine-tuned by neopolita, specifically designed for making decisions in Texas Hold'em poker. This model excels at preflop and postflop poker scenarios, demonstrating significant performance improvements over its base model on poker-specific benchmarks. Its primary strength lies in providing strategic guidance for poker gameplay.
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Overview
The neopolita/TexasHoldEm-Llama-3.2-1B-Instruct is a specialized 1 billion parameter language model, fine-tuned from the meta-llama/Llama-3.2-1B-Instruct base model. Its core purpose is to assist with decision-making in Texas Hold'em poker, covering both preflop and postflop scenarios.
Key Capabilities
- Poker Decision Support: Optimized for generating strategic advice and decisions in Texas Hold'em.
- Specialized Fine-tuning: Utilizes LoRA fine-tuning with
unsloth-mlxon theRZ412/PokerBenchdataset. - Performance Improvement: Demonstrates substantial gains over the base model in poker-specific tasks.
- Preflop: Achieves 83% accuracy, a +76% improvement.
- Postflop: Achieves 55% accuracy, a +42% improvement.
Good For
- Poker Strategy Analysis: Ideal for applications requiring automated poker decision support.
- Educational Tools: Can be integrated into tools designed to teach or analyze Texas Hold'em strategy.
- Game Simulation: Useful for simulating poker gameplay with intelligent agent decision-making.