---
license: mit
datasets:
- Taylor658/Electrohydrodynamics
base_model:
- mistralai/Mistral-Large-3-675B-Base-2512
language:
- en
tags:
- electrohydrodynamics
- hall-effect-thrusters
- plasma-physics
- computational-fluid-dynamics
- vllm
- mistral-common
- mistral-large-3
- mixture-of-experts
- 256k-context
- multimodal
library_name: vllm
pipeline_tag: text-generation
---

# ⚡ Electrohydrodynamics for Hall Effect Thrusters - Mistral Large 3 (v1.0)

> 🚀 Fine-tuned from **Mistral Large 3** for electrohydrodynamics and plasma physics research

## 🌟 Model Overview

**🏷️ Model Name:** `Taylor658/Electrohydrodynamics`  
**🔢 Version:** 1.0  
**🧠 Model Type:** Granular Mixture-of-Experts Language Model, domain fine-tuned  
**🌍 Language:** English  
**📄 License:** MIT (base model Apache 2.0, attribution retained)  
**🏗️ Base Model:** [`mistralai/Mistral-Large-3-675B-Base-2512`](https://huggingface.co/mistralai/Mistral-Large-3-675B-Base-2512)  

---

## 🔧 Model Details

- **👨‍💻 Developers:** A Taylor
- **🏗️ Model Architecture:** Mistral Large 3 granular Mixture-of-Experts transformer (673B language model, 39B active) with a 2.5B vision encoder
- **📊 Parameters:** 41B active / 675B total
- **⚡ Context Window:** 256,000 tokens (inherited from base model)
- **🖼️ Vision Input:** Supported by the base model; not a focus of this fine-tune
- **🔧 Native Function Calling:** Supported by the base model
- **📅 Release:** v1.0

---

## 🎯 Intended Use

### 🔬 Primary Applications:
- 🧪 **Aerospace Engineering:** Assist engineers and researchers in analyzing plasma and fluid flows in HET channels
- ⚡ **Electrohydrodynamics Research:** Support for understanding EHD phenomena in thrusters
- 🔬 **Computational Modeling:** Assistance with plasma fluid interaction modeling
- 📊 **Data Analysis:** Interpret long simulation reports within the 256k context
- 💻 **Code Generation:** Draft simulation scripts and analysis tools for review

### 💡 Usage Scenarios:
- 🧲 **Magnetic Field Analysis:** Discussing the influence of magnetic fields on electron mobility in thruster channels
- ⚡ **Ionization Dynamics:** Explaining ionization processes in the main thruster discharge channel
- 📈 **Simulation Interpretation:** Analyzing simulation datasets and theoretical results for efficiency optimization
- 🔬 **Plume Characteristics:** Discussing thruster plume behavior and performance metrics
- 💻 **Coding Assistance:** Drafting CFD and plasma simulation code
- 📊 **Long-Context Analysis:** Reading extended research papers and technical documentation

### 🚫 Out of Scope:
- 🛰️ Thruster design or flight qualification decisions without independent verification
- 🛠️ Any system where an incorrect output has physical consequences
- 🌐 Domains outside electric propulsion and plasma physics

---

## 📚 Training Data

**📁 Dataset Name:** `Taylor658/Electrohydrodynamics`

### 🔬 Dataset Description:
A synthetic dataset of textual explanations, theoretical derivations, and computational concepts covering fluid dynamics and plasma interactions in Hall Effect Thrusters. All records are generated; none are measured test stand data.

### 📊 Data Modalities:
- **📝 Text:** Technical explanations, research summaries, and theoretical analyses
- **💻 Code:** CFD simulation scripts and plasma modeling snippets
- **📈 Numerical:** Simulated performance metrics

---

## ⚙️ Training Procedure

### 🚀 Training Pipeline:
The model starts from **Mistral Large 3 Base** and undergoes the following fine-tuning:

1. **🎯 Domain-Specific Fine-Tuning:** Parameter adaptation using the electrohydrodynamics dataset
2. **🔄 Iterative Refinement:** Repeated training rounds with manual review of sampled outputs
3. **🧠 Long-Context Training:** Training examples include extended documents to exercise the context window

---

## 📏 Evaluation

Quantitative benchmarks are not yet published for v1.0. Evaluation to date is manual review of sampled outputs against the source dataset and standard Hall thruster relationships. Results will be added in a later version.

---

## 💡 How to Use

Mistral Large 3 requires a full node (B200 or H200 in FP8; H100 or A100 in NVFP4). The recommended path is serving with vLLM and querying through the OpenAI-compatible endpoint.

### 🔧 Serve:
```bash
vllm serve Taylor658/Electrohydrodynamics \
  --tokenizer_mode mistral \
  --max-model-len 262144 \
  --tensor-parallel-size 8
```

### 🔧 Query:
```python
from openai import OpenAI

client = OpenAI(api_key="EMPTY", base_url="http://localhost:8000/v1")
model = client.models.list().data[0].id

resp = client.chat.completions.create(
    model=model,
    temperature=0.15,
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain how the Hall parameter governs electron mobility in a Hall Effect Thruster discharge channel. State assumptions."}
    ],
)
print(resp.choices[0].message.content)
```

### 📝 Example Queries:
- ⚡ *"How does the Hall parameter affect electron mobility in a Hall Effect Thruster operating at 300V discharge voltage?"*
- 🔬 *"What are the primary factors influencing ionization efficiency in the thruster channel, and how do they interact?"*
- 📊 *"Summarize this simulation report and identify the parameters most sensitive to efficiency."*
- 💻 *"Draft a CFD simulation script for modeling plasma flow in a cylindrical HET channel."*

---

## ⚠️ Limitations

- **🔢 First Release:** v1.0 is a first release; behavior will change in later versions
- **🎯 Domain Specificity:** Optimized for Hall Effect Thruster fluid dynamics; may degrade outside this domain
- **🔬 Synthetic Data Foundation:** Trained exclusively on synthetic data; outputs must be validated against experimental results
- **📏 No Published Benchmarks:** Quantitative evaluation is pending
- **💾 Computational Resources:** 675B total parameters; requires a multi-GPU node for inference
- **📊 Long Context:** Quality may degrade toward the upper end of the 256k window

---

## 🤝 Ethical Considerations

- **🎓 Research Aid:** Intended as a research and educational tool; **not a substitute for expert judgment** in critical applications
- **✅ Accuracy Validation:** Users should validate model outputs against established literature and experimental results
- **🔒 Responsible Use:** Follow Mistral AI's usage guidelines
- **🌍 Environmental Impact:** Consider the computational cost of deploying a model of this size

---

## 🙏 Acknowledgements

- **🏢 Mistral AI:** For the Mistral Large 3 base model (Apache 2.0)
- **📊 Dataset:** A Taylor, electrohydrodynamics dataset
- **🔬 Research Community:** Hall Effect Thruster and plasma physics literature that informed the dataset

---

## 📜 License

- **📄 Model License:** MIT
- **🏗️ Base Model:** Mistral Large 3, Apache 2.0 (see [Mistral AI's model card](https://huggingface.co/mistralai/Mistral-Large-3-675B-Base-2512)); original notice retained
- **📊 Dataset License:** MIT

---

## 🔮 Future Work

- **📏 Benchmarks:** Publish quantitative evaluation against held-out problem sets
- **🧠 Magnetohydrodynamics:** Extend coverage to MHD modeling
- **📈 Boundary Conditions:** Better handling of variable mass flow rates and complex boundary conditions
- **🔬 Plasma-Wall Interaction:** Refinement of wall interaction reasoning
- **🖼️ Diagram Input:** Evaluate the base model's vision capability on thruster schematics
- **🌐 Real-world Validation:** Comparison against published test stand data

---

## 📞 Contact Information

**👨‍🚀 Author:** A Taylor  
**🔗 Profile:** [hf.co/Taylor658](https://huggingface.co/Taylor658)  
**📧 Support:** Hugging Face discussions tab on this repository  
**🏗️ Base Model:** [Mistral Large 3](https://huggingface.co/mistralai/Mistral-Large-3-675B-Base-2512)

---
*Built with ⚡ for the aerospace and plasma physics research community using Mistral's latest Large 2411 model*

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