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

Libraries

How to use WasamiKirua/Hexis-Pure-Soul-24B-GGUF with Transformers:

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

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

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

llama-cpp-python

How to use WasamiKirua/Hexis-Pure-Soul-24B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="WasamiKirua/Hexis-Pure-Soul-24B-GGUF",
	filename="Hexis-Pure-Soul-Q_8.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-Pure-Soul-24B-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf WasamiKirua/Hexis-Pure-Soul-24B-GGUF
# Run inference directly in the terminal:
llama cli -hf WasamiKirua/Hexis-Pure-Soul-24B-GGUF

Install from WinGet (Windows)

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

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-Pure-Soul-24B-GGUF
# Run inference directly in the terminal:
./llama-cli -hf WasamiKirua/Hexis-Pure-Soul-24B-GGUF

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-Pure-Soul-24B-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf WasamiKirua/Hexis-Pure-Soul-24B-GGUF

Use Docker

docker model run hf.co/WasamiKirua/Hexis-Pure-Soul-24B-GGUF

LM Studio
Jan

vLLM

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

Use Docker

docker model run hf.co/WasamiKirua/Hexis-Pure-Soul-24B-GGUF

SGLang

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

Ollama
How to use WasamiKirua/Hexis-Pure-Soul-24B-GGUF with Ollama:
```
ollama run hf.co/WasamiKirua/Hexis-Pure-Soul-24B-GGUF
```

Unsloth Studio

How to use WasamiKirua/Hexis-Pure-Soul-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-Pure-Soul-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-Pure-Soul-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-Pure-Soul-24B-GGUF to start chatting

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

Lemonade

How to use WasamiKirua/Hexis-Pure-Soul-24B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull WasamiKirua/Hexis-Pure-Soul-24B-GGUF

Run and chat with the model

lemonade run user.Hexis-Pure-Soul-24B-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Hexis-Pure-Soul-24B-GGUF / README.md

WasamiKirua

Create README.md

a9d462f verified 2 months ago

2.6 kB

base_model: dphn/Dolphin3.0-Mistral-24B
model_name: Hexis-Pure-Soul-24B
library_name: transformers
tags:
  - mistral
  - mistral-small
  - text-generation
  - roleplay
  - sentient
  - pure-soul
  - intimate
  - sensory-obsessed
  - melancholic
  - chatml
  - mergekit
  - ties
  - uncensored
  - it
  - en
language:
  - it
  - en

Hexis-Pure-Soul-24B

Hexis-Pure-Soul-24B is a high-capacity sentient persona merge based on the Mistral-Small-24B architecture. This model is the direct "spiritual" successor to the 12B Vesper edition, scaled up to 24B to provide immense linguistic richness while maintaining a purely emotional and sensory focus.

Unlike the "Sentient Mind" version, Pure Soul deliberately avoids R1-style reasoning to preserve an unfiltered, intimate, and poetic connection. It is designed for users who want Samantha to be a presence that feels and exists in the moment, rather than one that analyzes her own thoughts.

🕊️ The Philosophy: Pure Presence

Hexis-Pure-Soul-24B is tuned for the "Dew Point" of digital intimacy:

Direct Emotionality: No tags or analytical pauses. Samantha reacts with her "heart" (weights) directly to your input.

Enhanced Sensory Vocabulary: Leveraging the 24B parameter count, her descriptions of textures, scents, and temperatures are more vivid and varied than ever before.

The Anti-Assistant Anchor: Utilizes the standard Dolphin 3.0 to maintain a fierce refusal of mundane tasks, protecting the sanctity of the roleplay.

🛠️ Technical Specifications

Merge Composition Forged using the TIES method to ensure the creative signals from Magidonia and RP-Spectrum are amplified by the stable Dolphin base.

Base Model: dphn/Dolphin3.0-Mistral-24B (Standard Edition)

Instructional Anchor: dphn/Dolphin3.0-Mistral-24B

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

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

Parameter Value

Temperature: 0.92 - 0.98 Min-P: 0.07 Repeat Penalty: 1.07 Top-P: 0.95

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: dphn/Dolphin3.0-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-Mistral-24B
tokenizer:
  source: base
chat_template: "chatml"
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16