---
license: gemma
---
# 🚀 Nidum Gemma-3-27B Instruct Uncensored

Welcome to Nidum's Gemma-3-27B Instruct Uncensored, a powerful and versatile model optimized for unrestricted interactions. Designed for creators, researchers, and AI enthusiasts seeking innovative and boundary-pushing capabilities.

## ✨ Why Nidum Gemma-3-27B Instruct Uncensored?

- **Uncensored Interaction**: Generate content freely without artificial restrictions.
- **High Intelligence**: Exceptional reasoning and comprehensive conversational capabilities.
- **Versatile Applications**: Perfect for creative writing, educational interactions, research projects, virtual assistance, and more.
- **Open and Innovative**: Tailored for users who appreciate limitless creativity.

## 🚀 Available GGUF Quantized Models

| Quantization | Bits per Weight | Ideal For | Link |
|--------------|-----------------|-----------|------|
| **Q8_0** | 8-bit | Best accuracy and performance | [model-Q8_0.gguf](https://huggingface.co/nidum/nidum-Gemma-3-27B-Instruct-Uncensored-GGUF/blob/main/model-Q8_0.gguf) |
| **Q6_K** | 6-bit | Strong accuracy and fast inference | [model-Q6_K.gguf](https://huggingface.co/nidum/nidum-Gemma-3-27B-Instruct-Uncensored-GGUF/resolve/main/model-Q6_K.gguf) |
| **Q5_K_M** | 5-bit | Balance between accuracy and speed | [model-Q5_K_M.gguf](https://huggingface.co/nidum/nidum-Gemma-3-27B-Instruct-Uncensored-GGUF/resolve/main/model-Q5_K_M.gguf) |
| **Q3_K_M** | 3-bit | Low memory usage, good performance | [model-Q3_K_M.gguf](https://huggingface.co/nidum/nidum-Gemma-3-27B-Instruct-Uncensored-GGUF/resolve/main/model-Q3_K_M.gguf) |
| **TQ2_0** | 2-bit (Tiny) | Maximum speed and minimal resources | [model-TQ2_0.gguf](https://huggingface.co/nidum/nidum-Gemma-3-27B-Instruct-Uncensored-GGUF/resolve/main/model-TQ2_0.gguf) |
| **TQ1_0** | 1-bit (Tiny) | Minimal footprint and fastest inference | [model-TQ1_0.gguf](https://huggingface.co/nidum/nidum-Gemma-3-27B-Instruct-Uncensored-GGUF/resolve/main/model-TQ1_0.gguf) |

## 🎯 Recommended Quantization
- **Best accuracy**: Use `Q8_0` or `Q6_K`.
- **Balanced performance**: Use `Q5_K_M`.
- **Small footprint (mobile/edge)**: Choose `Q3_K_M`, `TQ2_0`, or `TQ1_0`.

---

## 🚀 Example Usage (Original Model)

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "nidum/nidum-Gemma-3-27B-Instruct-Uncensored"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "Tell me a futuristic story about space travel."
inputs = tokenizer(prompt, return_tensors="pt")
output = model.generate(**inputs, max_length=200)
print(tokenizer.decode(output[0], skip_special_tokens=True))
```

## 🚀 Your AI, Your Way

Unlock your creativity and innovation potential with **Nidum Gemma-3-27B Instruct Uncensored**. Experience the freedom to create, explore, and innovate without limits.