Qwen3-4B-MegaR3ASONER-v1/README.md

language, license, library_name, pipeline_tag, base_model, base_model_relation, tags, datasets

language	license	library_name	pipeline_tag	base_model	base_model_relation	tags	datasets
en	other	transformers	text-generation	Qwen/Qwen3-4B-Thinking-2507	finetune	qwen qwen3 reasoning chain-of-thought text-generation bf16 merged	HuggingFaceH4/Bespoke-Stratos-17k nvidia/OpenMathReasoning nvidia/OpenCodeReasoning nvidia/OpenScienceReasoning-2 lordx64/reasoning-distill-opus-4-7-max-sft

Qwen3-4B-MegaR3ASONER-v1

A full merged reasoning model created by merging the MegaR3ASONER LoRA into Qwen/Qwen3-4B-Thinking-2507.

Model type

This repository contains the complete merged Transformers model, not only the PEFT adapter. It can be loaded directly without PeftModel.

• Base model: Qwen/Qwen3-4B-Thinking-2507
• Merge dtype: BF16
• Adapter source: RexTRO111/Qwen3-4B-MegaR3ASONER-LoRA-v1
• Training hardware: NVIDIA A10G on Modal
• Merge hardware: NVIDIA A10G on Modal

Preliminary evaluation

On the first 100 examples selected by EleutherAI's gsm8k_cot task:

• Flexible extraction exact match: 88%
• Strict match: 83%

This was a limited 100-question run, not a full GSM8K score and not a controlled base-versus-fine-tune comparison.

Loading

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "RexTRO111/Qwen3-4B-MegaR3ASONER-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
model.eval()

Limitations

• It may produce an incorrect intermediate thought before correcting itself.
• It can overthink simple prompts.
• Long reasoning traces increase latency and cost.
• Benchmark contamination has not been exhaustively ruled out.
• Verify answers before high-stakes use.

Licensing note

The Qwen base model and every training dataset retain their own licenses and upstream terms. Review all applicable terms before redistribution or commercial use.