Text Generation
PEFT
Safetensors
game-theory
grpo
reinforcement-learning
reasoning
qwen2.5
lora
conversational
Eval Results (legacy)
Instructions to use Alogotron/GameTheory-Reasoner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Alogotron/GameTheory-Reasoner with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/beta1/gt-training/phase1_merged") model = PeftModel.from_pretrained(base_model, "Alogotron/GameTheory-Reasoner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b510d6bebeae06a4daf5b35cf5b1c586a308ab568b1845e17900e104fb11c9e5
- Size of remote file:
- 11.4 MB
- SHA256:
- f7f96da3a872b5e901575b2067c744ad336c3a3d77a21584d20024557b1bd7f0
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