Instructions to use Phr00t/Phr00tyMix-v3-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Phr00t/Phr00tyMix-v3-32B with Transformers:

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

pipe = pipeline("text-generation", model="Phr00t/Phr00tyMix-v3-32B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Phr00t/Phr00tyMix-v3-32B")
model = AutoModelForCausalLM.from_pretrained("Phr00t/Phr00tyMix-v3-32B", 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 Phr00t/Phr00tyMix-v3-32B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Phr00t/Phr00tyMix-v3-32B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Phr00t/Phr00tyMix-v3-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Phr00t/Phr00tyMix-v3-32B

SGLang

How to use Phr00t/Phr00tyMix-v3-32B 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 "Phr00t/Phr00tyMix-v3-32B" \
    --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": "Phr00t/Phr00tyMix-v3-32B",
		"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 "Phr00t/Phr00tyMix-v3-32B" \
        --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": "Phr00t/Phr00tyMix-v3-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Phr00t/Phr00tyMix-v3-32B with Docker Model Runner:
```
docker model run hf.co/Phr00t/Phr00tyMix-v3-32B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

This model has been replaced by: Phr00tyMix v4

WARNING: This model is slightly incoherent and v4 should be used instead.

Phr00tyMix-v3-32B

After many, many failed attempts... I finally got the Phr00tyMix v3 I was looking for! I find this more creative and spicy, while perhaps increasing smarts and obediency over Phr00tyMix v2 too (edit: mixed bag, use v4 instead). If you ask it to be uncensored, it will be.

The goal: smart, obedient, creative, spicy, uncensored and coherent -- my initial testing shows this tops all of my previous mixes.

I recommend a high temperature (1.5) and a high MinP (0.1), but play around as you wish.

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the Model Stock merge method using Phr00t/Phr00tyMix-v2-32B as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

merge_method: model_stock
base_model: Phr00t/Phr00tyMix-v2-32B
dtype: bfloat16
models:
  - model: huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated 
  - model: Delta-Vector/Archaeo-32B-KTO
  - model: trashpanda-org/QwQ-32B-Snowdrop-v0
  - model: allura-org/Qwen2.5-32b-RP-Ink
  - model: arcee-ai/Virtuoso-Medium-v2
tokenizer:
  source: "Delta-Vector/Archaeo-32B-KTO"