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base_model: Qwen/Qwen2.5-3B-Instruct
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:Qwen/Qwen2.5-3B-Instruct
- lora
- sft
- transformers
- trl
- german
- english
- aether
- aether-2.5
- gguf
license: apache-2.0
language:
- de
- en
---
# Aether 2.5 Pro
Aether 2.5 Pro is the strongest model in the Aether 2.5 series so far.
It is a fine-tuned version of **Qwen2.5-3B-Instruct**, trained with TRL + PEFT (LoRA) on a higher-quality and more diverse dataset than previous versions.
Compared to the standard Aether 2.5, the Pro version offers:
- Better reasoning
- Improved instruction following
- Stronger multilingual performance (German + English)
- Higher overall response quality while staying efficient for local use
> 🖥️ **Want an easy way to run it?**
> Download **MonoAIStudio** – our local chat application.
> It comes pre-installed with **Aether 2.5**, **Aether 2.5 Pro** and **Aether 2.5 Coder**.
> 👉 [Download MonoAIStudio.zip](https://huggingface.co/Maxilicious20/Aether-2.5-Pro/resolve/main/MonoAIStudio.zip)
> 🚀 **Looking for GGUF versions?**
> 👉 **[Maxilicious20/Aether-2.5-Pro-GGUF](https://huggingface.co/Maxilicious20/Aether-2.5-Pro-GGUF)**
## Model Details
### Model Description
- **Developed by:** Maxilicious20 (Mono AI Studio)
- **Model type:** Causal Language Model (LoRA Adapter)
- **Language(s):** German, English
- **License:** Apache-2.0
- **Finetuned from model:** [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct)
## Uses
### Direct Use
Aether 2.5 Pro is designed for:
- High-quality conversational AI
- Reasoning and problem solving
- Instruction following
- General text generation
- Local deployment on consumer hardware
### Easy Local Usage (Recommended)
The easiest way to use this model is with **MonoAIStudio**:
1. Download `MonoAIStudio.zip`
2. Extract it
3. Run `MonoAIStudio.exe`
4. All Aether 2.5 models are already included
### Quantized & GGUF Models
For use with LM Studio, Ollama, llama.cpp, etc.:
* 📦 **GGUF Repository:** [Maxilicious20/Aether-2.5-Pro-GGUF](https://huggingface.co/Maxilicious20/Aether-2.5-Pro-GGUF)
## How to Use (Python)
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model_id = "Qwen/Qwen2.5-3B-Instruct"
adapter_id = "Maxilicious20/Aether-2.5-Pro"
tokenizer = AutoTokenizer.from_pretrained(base_model_id)
base_model = AutoModelForCausalLM.from_pretrained(
base_model_id,
torch_dtype=torch.bfloat16,
device_map="auto"
)
model = PeftModel.from_pretrained(base_model, adapter_id)
messages = [
{"role": "system", "content": "You are Aether 2.5 Pro, a highly capable AI assistant developed by Mono AI Studio."},
{"role": "user", "content": "Explain the difference between supervised and unsupervised learning in simple terms."}
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)) |