| | --- |
| | base_model: unsloth/gpt-oss-120b-unsloth-bnb-4bit |
| | tags: |
| | - text-generation-inference |
| | - transformers |
| | - unsloth |
| | - gpt_oss |
| | - mathematics |
| | - olympiad-math |
| | - reasoning |
| | - chain-of-thought |
| | license: apache-2.0 |
| | language: |
| | - en |
| | datasets: |
| | - HuggingFaceH4/Multilingual-Thinking |
| | - brando/olympiad-bench-imo-math-boxed-825-v2-21-08-2024 |
| | - Goedel-LM/MathOlympiadBench |
| | - hf-imo-colab/olympiads-ref-base-math-word |
| | --- |
| | |
| | # GPT-OSS-120B Olympiad Reasoning |
| |
|
| | This model is a specialized fine-tune of **OpenAI's GPT-OSS 120B** (4-bit quantized by Unsloth). It is designed for high-level mathematical reasoning, complex problem solving, and long-form "Thinking" processes. |
| |
|
| | - **Developed by:** Azmainadeeb |
| | - **Base Model:** unsloth/gpt-oss-120b-unsloth-bnb-4bit |
| | - **Architecture:** Mixture-of-Experts (MoE) with 117B total and 5.1B active parameters. |
| | - **License:** Apache-2.0 |
| |
|
| | [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
| |
|
| | ## 🌟 Model Highlights |
| | This model uses the **Harmony Response Format** natively, allowing for a distinct separation between "internal reasoning" and "final response." By fine-tuning on a mixture of thinking traces and competition-grade math, the model exhibits improved logical consistency and accuracy in STEM domains. |
| |
|
| | ### Capabilities: |
| | * **Deep Reasoning:** Leverages the `Multilingual-Thinking` dataset to maintain a coherent chain-of-thought. |
| | * **Competition Math:** Optimized for International Mathematical Olympiad (IMO) and AIME-style problems. |
| | * **Variable Effort:** Supports the `reasoning_effort` parameter (low, medium, high) to balance speed and accuracy. |
| |
|
| |
|
| |
|
| | ## 📊 Training Data |
| | The model was trained on a high-diversity mixture of reasoning and mathematical datasets: |
| |
|
| | 1. **[HuggingFaceH4/Multilingual-Thinking](https://huggingface.co/datasets/HuggingFaceH4/Multilingual-Thinking):** Provides the foundational "thinking" behavior and internal monologue. |
| | 2. **[brando/olympiad-bench-imo-math](https://huggingface.co/datasets/brando/olympiad-bench-imo-math-boxed-825-v2-21-08-2024):** High-difficulty math competition problems. |
| | 3. **[Goedel-LM/MathOlympiadBench](https://huggingface.co/datasets/Goedel-LM/MathOlympiadBench):** Challenging math benchmark problems. |
| | 4. **[hf-imo-colab/olympiads-ref-base-math-word](https://huggingface.co/datasets/hf-imo-colab/olympiads-ref-base-math-word):** Diverse word problems and solutions. |
| | 5. **Kaggle External Math Data:** Curated datasets from AoPS, AIMO, and OlympiadBench for extra-domain coverage. |
| |
|
| | ## 🛠 Usage Instructions |
| | This model is optimized for use with the **Unsloth** library and Hugging Face's `transformers`. |
| |
|
| | ### Quick Inference Example |
| | ```python |
| | from unsloth import FastLanguageModel |
| | import torch |
| | |
| | model, tokenizer = FastLanguageModel.from_pretrained( |
| | model_name = "Azmainadeeb/gpt-oss-120b-olympiad", # Replace with your repo ID |
| | max_seq_length = 2048, |
| | load_in_4bit = True, |
| | ) |
| | |
| | messages = [ |
| | {"role": "user", "content": "Let n be a positive integer such that n^2 + 3n + 2 is a perfect square. Find all such n."} |
| | ] |
| | |
| | input_ids = tokenizer.apply_chat_template( |
| | messages, |
| | add_generation_prompt = True, |
| | reasoning_effort = "medium", # Options: low, medium, high |
| | return_tensors = "pt" |
| | ).to("cuda") |
| | |
| | outputs = model.generate(input_ids, max_new_tokens = 1024) |
| | print(tokenizer.decode(outputs[0])) |
