---
license: apache-2.0
datasets:
- nvidia/OpenScienceReasoning-2
language:
- en
base_model:
- Qwen/Qwen3-1.7B
pipeline_tag: text-generation
library_name: transformers
tags:
- trl
- text-generation-inference
- medical
- science
---

![1.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/8pw-8QKAN4gLRJLy2k9Nc.png)

# **OpenScienceReasoning-Qwen-e10**

> OpenScienceReasoning-Qwen-e10 is a high-efficiency, science-focused reasoning model fine-tuned on **Qwen3-1.7B** using the [**nvidia/OpenScienceReasoning-2**](https://huggingface.co/datasets/nvidia/OpenScienceReasoning-2) dataset. It incorporates **10,000 distinct entries** for scientific reasoning, chain-of-thought exploration, and analytical problem solving.
> The model blends symbolic precision, scientific logic, and structured output fluency—making it an ideal tool for researchers, educators, and developers seeking advanced reasoning under constrained compute.

> \[!note]
> GGUF: [https://huggingface.co/prithivMLmods/OpenScienceReasoning-Qwen-e10-GGUF](https://huggingface.co/prithivMLmods/OpenScienceReasoning-Qwen-e10-GGUF)

---

## **Key Features**

1. **Scientific Reasoning & Chain-of-Thought**
   Fine-tuned on **10,000 curated entries** from the **OpenScienceReasoning-2** dataset, designed to enhance step-by-step analytical reasoning in science and mathematics.

2. **Advanced Code Reasoning & Generation**
   Supports multi-language coding with explanations, optimization hints, and error detection—ideal for algorithm synthesis, debugging, and prototyping.

3. **Mathematical & Scientific Problem Solving**
   Performs analytical reasoning in physics, biology, chemistry, and mathematics—explaining concepts, solving equations, and handling symbolic derivations.

4. **Hybrid Symbolic-AI Thinking**
   Combines structured logic, chain-of-thought reasoning, and open-ended inference, delivering robust performance on STEM-related tasks.

5. **Structured Output Mastery**
   Seamlessly generates output in **LaTeX**, **Markdown**, **JSON**, **CSV**, and **YAML**, suited for technical documentation, research papers, and structured data.

6. **Optimized Lightweight Footprint for Versatile Deployment**
   Balances performance and efficiency, making it deployable on **mid-range GPUs**, **offline clusters**, and **edge AI systems**.

---

## **Quickstart with Transformers**

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "prithivMLmods/OpenScienceReasoning-Qwen-e10"

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

prompt = "Explain the difference between Newtonian mechanics and quantum mechanics with examples."

messages = [
    {"role": "system", "content": "You are a scientific tutor skilled in reasoning, math, and coding."},
    {"role": "user", "content": prompt}
]

text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
```

---

## **Intended Use**

* Scientific tutoring, computational reasoning, and mathematical education
* Research assistant for physics, chemistry, biology, and interdisciplinary domains
* Structured technical data generation in multiple formats
* STEM-focused chatbot or API for research and education tools
* Deployment in mid-resource environments requiring high reasoning fidelity

## **Limitations**

* Not tuned for general-purpose or long-form creative writing
* Context limitations may hinder multi-document or full codebase analysis
* Specialized for scientific and technical reasoning—general chat may underperform
* Prioritizes structured logic over casual or emotional tone generation