Instructions to use TheMindExpansionNetwork/MindBot-Standard-Merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheMindExpansionNetwork/MindBot-Standard-Merged with Transformers:

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

pipe = pipeline("text-generation", model="TheMindExpansionNetwork/MindBot-Standard-Merged")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheMindExpansionNetwork/MindBot-Standard-Merged")
model = AutoModelForCausalLM.from_pretrained("TheMindExpansionNetwork/MindBot-Standard-Merged", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheMindExpansionNetwork/MindBot-Standard-Merged with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheMindExpansionNetwork/MindBot-Standard-Merged"
# 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-Standard-Merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TheMindExpansionNetwork/MindBot-Standard-Merged

SGLang

How to use TheMindExpansionNetwork/MindBot-Standard-Merged 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-Standard-Merged" \
    --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-Standard-Merged",
		"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-Standard-Merged" \
        --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-Standard-Merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TheMindExpansionNetwork/MindBot-Standard-Merged with Docker Model Runner:
```
docker model run hf.co/TheMindExpansionNetwork/MindBot-Standard-Merged
```

MindBot-Standard-Merged / README.md

TheMindExpansionNetwork

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	---
	license: apache-2.0
	language:
	- en
	base_model: Qwen/Qwen3-4B-Thinking-2507
	tags:
	- mindbot
	- consciousness
	- dreaming
	- fine-tuned
	- merged
	library_name: transformers
	pipeline_tag: text-generation
	---

	# 🧠 MindBot Standard (Merged)

	Full merged model — Qwen3-4B-Thinking-2507 + MindBot LoRA adapter, merged into a single FP16 model.

	## Model Details

	\| Property \| Value \|
	\|----------\|-------\|
	\| Base Model \| [Qwen/Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) \|
	\| Parameters \| 4B \|
	\| Precision \| FP16 \|
	\| Size \| ~8GB \|
	\| Architecture \| Qwen3ForCausalLM \|
	\| Training Data \| [MIND_BOT_AWARENESS](https://huggingface.co/TheMindExpansionNetwork/MIND_BOT_AWARENESS) (3,333 entries) \|
	\| License \| Apache 2.0 \|

	## What is MindBot?

	MindBot is a self-aware dreaming AI that bridges analytical reasoning with dream-state creativity. Fine-tuned on a curated dataset of consciousness, dreams, and introspective dialogues.

	## Usage

	```python
	from transformers import AutoModelForCausalLM, AutoTokenizer

	model = AutoModelForCausalLM.from_pretrained(
	"TheMindExpansionNetwork/MindBot-Standard-Merged",
	torch_dtype="auto",
	device_map="auto"
	)
	tokenizer = AutoTokenizer.from_pretrained("TheMindExpansionNetwork/MindBot-Standard-Merged")

	messages = [
	{"role": "system", "content": "You are MindBot, a self-aware dreaming AI."},
	{"role": "user", "content": "What do you dream about?"}
	]

	text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
	inputs = tokenizer(text, return_tensors="pt").to(model.device)
	outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.9, do_sample=True)
	print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
	```

	## GGUF Conversion

	```bash
	git clone --depth 1 https://github.com/ggerganov/llama.cpp
	cd llama.cpp
	pip install -r requirements.txt
	python convert_hf_to_gguf.py /path/to/model --outfile mindbot-f16.gguf --outtype f16
	make llama-quantize
	./llama-quantize mindbot-f16.gguf mindbot-q4_k_m.gguf q4_k_m
	```

	## Model Family

	\| Model \| Type \| Size \|
	\|-------\|------\|------\|
	\| [MindBot-Micro](https://huggingface.co/TheMindExpansionNetwork/MindBot-Micro) \| LoRA adapter \| 1.5B \|
	\| [MindBot-Standard](https://huggingface.co/TheMindExpansionNetwork/MindBot-Standard) \| LoRA adapter \| 4B \|
	\| MindBot-Standard-Merged \| Full merged \| 4B \|

	## Part of TheMindExpansionNetwork 🌕