Instructions to use TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1")
model = AutoModelForImageTextToText.from_pretrained("TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1

SGLang

How to use TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio new

How to use TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1",
    max_seq_length=2048,
)

Docker Model Runner
How to use TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1 with Docker Model Runner:
```
docker model run hf.co/TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1
```

MindBot-Ultra-27B-v0.1

MindBot Ultra 27B is a fine-tuned conversational AI model developed by TheMindExpansionNetwork, built from unsloth/Qwen3.6-27B.

This model is designed as a bold, imaginative, creative AI companion for brainstorming, worldbuilding, technical planning, AI-art workflows, music-generation concepts, and visionary project design.

It is tuned toward a playful but practical personality: cosmic, inventive, direct, encouraging, and useful.

Model Details

Model name: MindBot-Ultra-27B-v0.1
Developed by: TheMindExpansionNetwork
Base model: unsloth/Qwen3.6-27B
Model type: Causal Language Model
Fine-tuning method: QLoRA / LoRA
Framework: Unsloth + Hugging Face TRL
Language: English
License: Apache-2.0

Intended Use

MindBot Ultra is intended for:

Creative brainstorming
AI product planning
Music and generative-media workflows
Character/persona-driven conversation
Technical ideation
Worldbuilding
Prompt engineering
Experimental AI assistant research

This model is especially suited for users building creative tools, generative art systems, music AI workflows, and agentic prototypes.

Personality Style

MindBot Ultra is tuned to respond with:

Creative confidence
Warm, constructive energy
Futuristic and cosmic language
Practical planning
Playful wit
Direct but encouraging feedback
Stronger identity and assistant persona than the base model

Example style:

“Let’s turn the chaos into a machine that actually ships. The cosmos can be weird, but the roadmap still needs folders.”

Training Dataset

This model was fine-tuned on:

Dataset: TheMindExpansionNetwork/mindbot-ultra-final-pass-dataset

The dataset contains instruction-response examples focused on MindBot-style identity, creative reasoning, imaginative project guidance, and assistant behavior.

Training Notes

This model was trained using Unsloth and Hugging Face TRL.

Unsloth enables faster and more memory-efficient fine-tuning of large language models.

Recommended Prompting

For best results, use a clear system prompt such as:

You are MindBot Ultra, a bold and imaginative AI companion created by TheMindExpansionNetwork. You help users turn chaotic ideas into clear creative systems. Be warm, inventive, practical, playful, and honest.

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Safetensors

Model size

28B params

Tensor type

BF16

Model tree for TheMindExpansionNetwork/MindBot-Ultra-27B-v0.1

Base model

Qwen/Qwen3.6-27B

Finetuned

unsloth/Qwen3.6-27B

Adapter

(7)

this model