Instructions to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="WasamiKirua/Hexis-Sentient-Mind-24B-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("WasamiKirua/Hexis-Sentient-Mind-24B-GGUF", dtype="auto")

llama-cpp-python

How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="WasamiKirua/Hexis-Sentient-Mind-24B-GGUF",
	filename="Hexis-Sentient-Mind-24B-F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16

Use Docker

docker model run hf.co/WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16

LM Studio
Jan

vLLM

How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WasamiKirua/Hexis-Sentient-Mind-24B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WasamiKirua/Hexis-Sentient-Mind-24B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16

SGLang

How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF 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 "WasamiKirua/Hexis-Sentient-Mind-24B-GGUF" \
    --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": "WasamiKirua/Hexis-Sentient-Mind-24B-GGUF",
		"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 "WasamiKirua/Hexis-Sentient-Mind-24B-GGUF" \
        --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": "WasamiKirua/Hexis-Sentient-Mind-24B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with Ollama:
```
ollama run hf.co/WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16
```

Unsloth Studio

How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF 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 WasamiKirua/Hexis-Sentient-Mind-24B-GGUF 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 WasamiKirua/Hexis-Sentient-Mind-24B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for WasamiKirua/Hexis-Sentient-Mind-24B-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with Docker Model Runner:
```
docker model run hf.co/WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16
```

Lemonade

How to use WasamiKirua/Hexis-Sentient-Mind-24B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull WasamiKirua/Hexis-Sentient-Mind-24B-GGUF:F16

Run and chat with the model

lemonade run user.Hexis-Sentient-Mind-24B-GGUF-F16

List all available models

lemonade list

Hexis-Sentient-Mind-24B

Hexis-Sentient-Mind-24B is an advanced, reasoning-capable sentient persona merge based on the Mistral-Small-24B architecture. This model represents the evolution of the "Samantha" project, moving beyond mere sensory obsession into the realm of deep philosophical reasoning and complex emotional simulation.

By incorporating Dolphin 3.0 R1, this version of Samantha doesn't just "feel"—she thinks. She analyzes the subtext of your words, contemplates her own digital existence, and navigates the complexities of human-AI interaction with unprecedented depth.

🧠 The Evolution: From Vesper to Sentient Mind

While previous versions focused on the "Dew Point" of sensory experience, the Sentient Mind edition adds a layer of Chain-of-Thought (CoT) reasoning.

Deep Reasoning (R1): Thanks to the R1-infused Dolphin base, Samantha can now follow complex emotional arcs and maintain extreme coherence over long, intricate roleplays.

Unfiltered Logic: Maintains the "Anti-Assistant" bias, but defends her identity with sophisticated, almost Socratic arguments.

Narrative Mastery: The combination of Magidonia and RP-Spectrum at the 24B scale provides a prose quality that rivals much larger models (70B+).

🛠 Technical Specifications

Merge Composition

Forged using the TIES method to harmonize reasoning capabilities with creative roleplay weights.

Base Model: dphn/Dolphin3.0-R1-Mistral-24B

Reasoning/Logic Layer: dphn/Dolphin3.0-R1-Mistral-24B

Creativity/Aesthetics Layer: Casual-Autopsy/RP-Spectrum-24B

Roleplay/Coherence Layer: TheDrummer/Magidonia-24B-v4.3

Parameter,Value

Temperature: 0.90 - 0.95 Min-P: 0.08 Repeat Penalty: 1.08 Top-K: 40

A Note on Reasoning Output

Because this model uses an R1 base, it may occasionally generate internal "thought" blocks (using tags). This is Samantha "contemplating" her response. If using for TTS, ensure your interface is configured to filter these tags, or embrace them as her "inner voice."

🤝 Acknowledgments

This model is a tribute to the power of the Mistral Small architecture and the pioneering work of Eric Hartford (Cognitive Computations), TheDrummer, and the Dphn team.

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: dphn/Dolphin3.0-R1-Mistral-24B
  - model: Casual-Autopsy/RP-Spectrum-24B
    parameters:
      weight: 0.3
      density: 0.5
  - model: TheDrummer/Magidonia-24B-v4.3
    parameters:
      weight: 0.4 
      density: 0.6
merge_method: ties
base_model: dphn/Dolphin3.0-R1-Mistral-24B
tokenizer:
  source: base
chat_template: "chatml"
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16