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arithmetic-king-1b – AI Model by harshbhatt7585 | AlphaNeural AI

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harshbhatt7585/
arithmetic-king-1b

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text-generation

meta-llama/Llama-3.2-1B-Instruct

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Arithmetic King 1B

Repository id: harshbhatt7585/arithmetic-king-1b.

This model is a PEFT LoRA adapter trained with TRL GRPO on synthetic arithmetic episodes. It is tuned to answer in XML format:

<reasoning>...</reasoning>
<answer>...</answer>

Artifact Type

This repo contains adapter weights only (not full base model weights). Use with base model:

meta-llama/Llama-3.2-1B-Instruct

Training Configuration

Trainer: TRL GRPOTrainer
Fine-tuning method: LoRA (PEFT)
Environment: arithmetic reasoning episodes
Reward: correctness reward + XML-format bonus
Output style target: short reasoning plus final integer answer

Intended Use

Arithmetic-reasoning RLVR experiments
GRPO/LoRA workflow demonstrations
Adapter-centric fine-tuning studies on small instruct models

Limitations

Trained on synthetic arithmetic prompts only
Limited transfer to broader reasoning/math tasks
May produce malformed XML or incorrect answers
Not suitable for high-stakes use

Usage

python

from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel

base_id = "meta-llama/Llama-3.2-1B-Instruct"
adapter_id = "harshbhatt7585/arithmetic-king-1b"

tokenizer = AutoTokenizer.from_pretrained(base_id)
base_model = AutoModelForCausalLM.from_pretrained(base_id)
model = PeftModel.from_pretrained(base_model, adapter_id)

prompt = "Solve: (12 + 3) * 2. Return XML with <reasoning> and <answer>."
inputs = tokenizer(prompt, return_tensors="pt")
out = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(out[0], skip_special_tokens=True))

License

Adapter usage inherits base model license and terms:

meta-llama/Llama-3.2-1B-Instruct