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Model: nivektk/BullSolve Source: Original Platform
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README.md
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README.md
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---
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base_model: unsloth/llama-3.1-8B-Instruct-unsloth-bnb-4bit
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- gguf
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- text-generation
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- math
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- fine-tuning
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- llama-3
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license: apache-2.0
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language:
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- en
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dataset:
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- nivektk/math-augmented-dataset
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task_categories:
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- text-generation
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- question-answering
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size_categories:
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- 1K<n<10K
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model_name: BullSolve
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---
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# BullSolve: Fine-Tuned LLaMA 3 Model for Math Problem Solving
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## Model Description
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BullSolve is a fine-tuned version of `unsloth/llama-3.1-8B-Instruct-unsloth-bnb-4bit`, optimized for solving advanced math problems. The model was trained using LoRA adapters with the `nivektk/math-augmented-dataset`, which contains algebra problems and their solutions.
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This model is optimized for low VRAM usage and efficient inference while maintaining high accuracy in mathematical problem-solving tasks.
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# Training Data
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The model was fine-tuned using a subset of the [MATH Dataset](https://arxiv.org/abs/2103.03874), specifically the **Algebra** category, containing **1,006 validated examples**. This dataset, originally developed by Dan Hendrycks et al., consists of mathematical problems structured in JSON format, with attributes:
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- `problem`: Problem statement in text with LaTeX expressions.
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- `level`: Difficulty level (1 to 5).
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- `type`: Mathematical domain (e.g., Algebra, Geometry).
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- `solution`: Step-by-step solution in English.
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For fine-tuning, the dataset was preprocessed into ShareGPT format with the structure:
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```
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{question}[[
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Solution:
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{solution}
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]]
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```
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Additionally, a chat template was applied for better inference compatibility.
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## Training Configuration
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The model was trained using **Unsloth** with LoRA, optimizing memory efficiency and inference speed. Key parameters:
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- **Model**: `unsloth/llama-3.1-8B-Instruct-unsloth-bnb-4bit`
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- **Max Sequence Length**: 2048 tokens
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- **LoRA Config**:
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- Rank (`r`): 16
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- Alpha: 16
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- Dropout: 0
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- Target Modules: `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj`
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- **Training Arguments**:
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- Batch Size: 1
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- Gradient Accumulation: 4
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- Max Steps: 25
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- Learning Rate: 1e-4
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- Optimizer: AdamW (8-bit)
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- Weight Decay: 0.01
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- LR Scheduler: Linear
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## Inference
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BullSolve is optimized for fast inference and mathematical problem-solving. Example usage:
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```python
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from transformers import TextStreamer
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from unsloth import FastLanguageModel
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import torch
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model, tokenizer = FastLanguageModel.from_pretrained("nivektk/BullSolve")
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FastLanguageModel.for_inference(model)
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messages = [{"role": "user", "content": "Evaluate $\\log_{5^2}5^4$."}]
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input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to("cuda")
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text_streamer = TextStreamer(tokenizer, skip_prompt=True)
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_ = model.generate(input_ids, streamer=text_streamer, max_new_tokens=2000, pad_token_id=tokenizer.eos_token_id)
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```
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## Model Usage
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This model is suitable for:
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- Math tutoring and automated problem-solving
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- AI-assisted mathematical reasoning
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- Education-based chatbot assistants
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## Limitations
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- The model is trained only on algebra problems and may not generalize well to other areas of mathematics.
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- It is optimized for inference efficiency rather than large-scale fine-tuning.
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## Acknowledgments
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- **Unsloth** for efficient LoRA fine-tuning
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- **MATH Dataset** by Dan Hendrycks for problem-solving benchmarks
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## Citation
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If you use this model, please cite:
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```bibtex
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@article{BullSolve2025,
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title={BullSolve: Fine-Tuned LLaMA 3 for Math Problems},
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authors={Kevin Fabio Ramos López and Kevin Camilo Rincon Bohorquez and Nolhan Dumoulin},
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year={2025},
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journal={Hugging Face Models}
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}
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```
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# Uploaded model
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- **Developed by:** nivektk
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/llama-3.1-8B-Instruct-unsloth-bnb-4bit
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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