GPT-OSS-20B-AceReason-Math

GPT-OSS-20B (Finetuned & Merged)

• Author: ShahzebKhoso
• License: apache-2.0
• Base Model: unsloth/gpt-oss-20b
• Frameworks: Unsloth, Hugging Face Transformers

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📌 Model Details

This model is a finetuned and merged version of GPT-OSS-20B.
It was trained on the nvidia/AceReason-Math for solving mathematical problems.

Training used LoRA adapters with Unsloth for efficient optimization, then merged back into the base model using save_pretrained_merged.

Compared to the base:

• ✅ 2× faster training with Unsloth optimizations
• ✅ Memory efficient (4-bit training support)
• ✅ Ready for reasoning-style inference

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🚀 Usage

You can use this model as a chat model with reasoning-style prompts. Example:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "ShahzebKhoso/GPT-OSS-20B-AceReason-Math"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")

messages = [
    {"role": "system", "content": "You are a helpful AI that explains mathematical reasoning step by step."},
    {"role": "user", "content": "Solve x^5 + 3x^4 - 10 = 3."},
]

inputs = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt = True,
    return_tensors = "pt",
    return_dict = True,
    reasoning_effort = "medium",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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📊 Training

• Base: GPT-OSS-20B (unsloth/gpt-oss-20b)
• Dataset: AceReason-Math Splits: Train: 40,163 Validation: 4,463 Test: 4,963
• Method: Parameter-Efficient Fine-Tuning (LoRA)
• LoRA Config: r=8, alpha=16, dropout=0
• Merge: save_pretrained_merged from Unsloth
• Epochs: 3
• Training Time: ~32 hours

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❤️ Acknowledgements

This model was trained & merged using Unsloth.
<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>