codertrish/Finetuned-gemma3-270m-chess-merged

Gemma-3 270M — Chess Coach (Merged FP16)

Author: @codertrish
Base model: unsloth/gemma-3-270m-it
Type: Merged FP16 checkpoint (LoRA deltas baked into base — no adapters needed)
Task: Conversational chess tutoring (rules, beginner principles, simple reasoning)

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TL;DR

• This is a plug-and-play Gemma-3 (270M) checkpoint specialized for chess coaching.
• It was fine-tuned via LoRA on a subset of Thytu/ChessInstruct, then merged to FP16.
• Load directly with transformers and chat using the Gemma-3 chat template.

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✨ Intended Use

• Direct use: Explain chess rules, beginner opening principles, basic tactics, and high-level strategy in plain text.
• Downstream use: As a small assistant embedded in notebooks, tutorials, or beginner-level chess learning tools.

Out-of-scope: Engine-level move search, advanced calculation, or authoritative evaluations of complex positions. For serious analysis, use a dedicated chess engine (e.g., Stockfish) and verify claims.

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🔧 How to Use

The model expects Gemma-3 chat formatting. Use apply_chat_template before generation.

Minimal example (Transformers)

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

REPO = "codertrish/Finetuned-gemma3-270m-chess-merged"

tok   = AutoTokenizer.from_pretrained(REPO)
model = AutoModelForCausalLM.from_pretrained(REPO, torch_dtype="bfloat16", device_map="auto")

pipe = pipeline("text-generation", model=model, tokenizer=tok, return_full_text=False)

def chat(messages, **gen_kwargs):
    prompt = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
    eot_id = tok.convert_tokens_to_ids("<end_of_turn>")
    out = pipe(
        prompt,
        eos_token_id=eot_id,
        max_new_tokens=200,
        do_sample=False,         # deterministic; set True for sampling
        **gen_kwargs,
    )[0]["generated_text"]
    return out.strip()

messages = [
    {"role":"system","content":"You are a helpful chess coach. Answer in plain text, 3 concise bullets."},
    {"role":"user","content":"What are the main opening principles?"},
]
print(chat(messages))