nuriyev/chess-reasoning
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How to use nuriyev/chess-reasoner-lora with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("nuriyev/chess-reasoner-lora", dtype="auto")How to use nuriyev/chess-reasoner-lora with PEFT:
Task type is invalid.
How to use nuriyev/chess-reasoner-lora with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nuriyev/chess-reasoner-lora to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nuriyev/chess-reasoner-lora to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nuriyev/chess-reasoner-lora to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="nuriyev/chess-reasoner-lora",
max_seq_length=2048,
)LoRA adapter for chess move prediction with structured reasoning output.
Merged model: nuriyev/chess-reasoner
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507")
model = PeftModel.from_pretrained(base, "nuriyev/chess-reasoner-lora")
tokenizer = AutoTokenizer.from_pretrained("nuriyev/chess-reasoner-lora")
| Parameter | Value |
|---|---|
| Rank | 32 |
| Alpha | 64 |
| Target Modules | q, k, v, o, gate, up, down proj |
Trained with Unsloth. Next step: GRPO with Stockfish rewards.