Instructions to use Phr00t/Phr00tyMix-v2-32B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Phr00t/Phr00tyMix-v2-32B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Phr00t/Phr00tyMix-v2-32B-GGUF", dtype="auto")

llama-cpp-python

How to use Phr00t/Phr00tyMix-v2-32B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Phr00t/Phr00tyMix-v2-32B-GGUF",
	filename="Phr00tyMix-v2-32B-imat-IQ4_XS.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Phr00t/Phr00tyMix-v2-32B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M

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 Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M

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 Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use Phr00t/Phr00tyMix-v2-32B-GGUF with Ollama:
```
ollama run hf.co/Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M
```

Unsloth Studio

How to use Phr00t/Phr00tyMix-v2-32B-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 Phr00t/Phr00tyMix-v2-32B-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 Phr00t/Phr00tyMix-v2-32B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Phr00t/Phr00tyMix-v2-32B-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use Phr00t/Phr00tyMix-v2-32B-GGUF with Docker Model Runner:
```
docker model run hf.co/Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M
```

Lemonade

How to use Phr00t/Phr00tyMix-v2-32B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Phr00t/Phr00tyMix-v2-32B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Phr00tyMix-v2-32B-GGUF-Q4_K_M

List all available models

lemonade list

This model has been replaced by Phr00tyMix v3

Phr00tyMix-v2-32B

The goal: smart, obedient, uncensored, coherent roleplay and creative storywriting. I think this is a significant improvement over Phr00tyMix-v1. This model is more uncensored and pays much better attention to details.

I picked these models mostly for creative purposes that do not force thinking into responses:

ArliAI/QwQ-32B-ArliAI-RpR-v4 (for smart creativity and longer context)
allura-org/Qwen2.5-32b-RP-Ink ("cursed" roleplay support)
Delta-Vector/Hamanasu-Magnum-QwQ-32B (solid instruct creative finetune)
Sao10K/32B-Qwen2.5-Kunou-v1 (solid Qwen roleplay finetune)
nbeerbower/EVA-Gutenberg3-Qwen2.5-32B (mix of many solid writing finetunes)

The base model is huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated for an uncensored and very smart foundation.

I dropped the "LongWriter Zero" because it didn't seem to write very well when testing directly. I also dropped ROMBOS as the DeepSeek-R1-Distill appears to have enough brains as a foundation.

I've been very impressed with my (limited) testing of it thus far (formatted script writing, uncensored testing, reasoning etc.).

These are the GGUFs for the original model.

Merge Details

Configuration

The following YAML configuration was used to produce this model:

merge_method: model_stock
base_model: huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated
dtype: bfloat16
models:
  - model: nbeerbower/EVA-Gutenberg3-Qwen2.5-32B
  - model: Delta-Vector/Hamanasu-Magnum-QwQ-32B
  - model: ArliAI/QwQ-32B-ArliAI-RpR-v4
  - model: Sao10K/32B-Qwen2.5-Kunou-v1
  - model: allura-org/Qwen2.5-32b-RP-Ink

Downloads last month: 131

GGUF

Model size

33B params

Architecture

qwen2

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

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