# 🦙 Qylis / Llama-3.2-3B-Tuned
**A fine-tuned Llama 3.2 3B model by [Qylis](https://qylis.com)**
[](https://huggingface.co/meta-llama/Llama-3.2-3B)
[](https://qylis.com)
[](https://www.llama.com/llama3_2/license/)
[](https://huggingface.co/qylis)
---
## 📖 Model Overview
`qylis/llama3.2-3b-tuned` is a fine-tuned version of Meta's [Llama 3.2 3B](https://huggingface.co/meta-llama/Llama-3.2-3B), developed and maintained by **Qylis**. This model has been adapted for enhanced instruction-following and domain-specific performance, leveraging Qylis's proprietary fine-tuning pipeline.
| Property | Details |
|---|---|
| **Base Model** | meta-llama/Llama-3.2-3B |
| **Model Type** | Causal Language Model (CLM) |
| **Architecture** | LlamaForCausalLM |
| **Parameters** | ~3 Billion |
| **Fine-tuned by** | Qylis |
| **Language** | English |
| **License** | Llama 3.2 Community License |
---
## 🚀 Quick Start
### Installation
```bash
pip install transformers torch accelerate
```
### Inference
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "qylis/llama3.2-3b-tuned"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto"
)
prompt = "Your prompt here"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=512,
temperature=0.7,
top_p=0.9,
do_sample=True,
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```
### Pipeline API
```python
from transformers import pipeline
pipe = pipeline(
"text-generation",
model="qylis/llama3.2-3b-tuned",
torch_dtype="auto",
device_map="auto"
)
result = pipe("Your prompt here", max_new_tokens=256)
print(result[0]["generated_text"])
```
---
## 🎯 Intended Use
This model is intended for:
- **Instruction following** — Responding to natural language instructions
- **Text generation** — Generating coherent and contextually relevant text
- **Domain-specific tasks** — Applications fine-tuned by Qylis for specific use cases
- **Research and development** — Experimentation with fine-tuned LLMs
### Out-of-Scope Use
- Generating harmful, abusive, or misleading content
- High-stakes decision making without human oversight
- Use in applications requiring absolute factual accuracy without verification
---
## 🏋️ Training Details
| Property | Details |
|---|---|
| **Base Model** | meta-llama/Llama-3.2-3B |
| **Fine-tuning Method** | Supervised Fine-Tuning (SFT) |
| **Fine-tuned by** | Qylis |
| **Framework** | HuggingFace Transformers / PEFT |
> 📝 Additional training details, dataset information, and hyperparameters will be updated as documentation is finalized.
---
## 📊 Evaluation
> Benchmark results and evaluation metrics will be published here. Stay tuned for updates from the Qylis team.
---
## ⚠️ Limitations & Bias
Like all large language models, this model may:
- **Hallucinate** — Generate plausible-sounding but factually incorrect information
- **Reflect training biases** — Exhibit biases present in the training data
- **Struggle with long contexts** — Performance may degrade with very long inputs
- **Lack real-time knowledge** — No access to information beyond the training cutoff
Always validate outputs in production settings, especially for critical applications.
---
## 📜 License
This model is based on **Meta's Llama 3.2** and is subject to the [Llama 3.2 Community License Agreement](https://www.llama.com/llama3_2/license/). By using this model, you agree to the terms of that license.
> ⚠️ **Naming Requirement:** Per the Llama 3.2 Community License, any fine-tuned model distributed publicly must include **"Llama"** at the beginning of its name (e.g., `Llama-Qylis-3.2-3B-Tuned`). Please ensure your model name on HuggingFace complies with this requirement.
---
## 🤝 About Qylis
**Qylis** is building next-generation AI solutions, from fine-tuned language models to production-ready AI applications.
🌐 [qylis.com](https://qylis.com) | 🤗 [HuggingFace](https://huggingface.co/qylis) | 📧 [Contact Us](mailto:hello@qylis.com)
---
## 📬 Citation
If you use this model in your research or application, please cite:
```bibtex
@misc{qylis2024llama32tuned,
title = {Qylis Llama-3.2-3B-Tuned},
author = {Qylis},
year = {2024},
publisher = {HuggingFace},
howpublished = {\url{https://huggingface.co/qylis/llama3.2-3b-tuned}}
}
```
