Instructions to use redrix/matricide-12B-Unslop-Unleashed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use redrix/matricide-12B-Unslop-Unleashed with Transformers:

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

pipe = pipeline("text-generation", model="redrix/matricide-12B-Unslop-Unleashed")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("redrix/matricide-12B-Unslop-Unleashed")
model = AutoModelForCausalLM.from_pretrained("redrix/matricide-12B-Unslop-Unleashed")
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 redrix/matricide-12B-Unslop-Unleashed with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "redrix/matricide-12B-Unslop-Unleashed"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "redrix/matricide-12B-Unslop-Unleashed",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/redrix/matricide-12B-Unslop-Unleashed

SGLang

How to use redrix/matricide-12B-Unslop-Unleashed 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 "redrix/matricide-12B-Unslop-Unleashed" \
    --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": "redrix/matricide-12B-Unslop-Unleashed",
		"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 "redrix/matricide-12B-Unslop-Unleashed" \
        --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": "redrix/matricide-12B-Unslop-Unleashed",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use redrix/matricide-12B-Unslop-Unleashed with Docker Model Runner:
```
docker model run hf.co/redrix/matricide-12B-Unslop-Unleashed
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

A newer version of this model is available: redrix/matricide-12B-Unslop-Unleashed-v2

This Model is most likely broken.

This Discussion shows there's a token leak in a similar model. I forgot to specify a union tokenizer, although I don't know whether that's the exact cause.
I've released v2 here: redrix/matricide-12B-Unslop-Unleashed-v2
This version will be left up for archival purposes. But may get deleted if it's obtrusive.

matricide-12B-Unslop-Unleashed

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

This is my second merge. The goal was to introduce UnslopNemo to NemoMix to help combat the GPTisms Nemomix suffers under. Now that NuSLERP has been released, I might redo this and patricide with adjusted parameters.

Testing stage: early testing

I do not know how this model holds up over long term context. Early testing showed stability and viable answers. I am working on v2, as such I won't bother with further testing.

Parameters

Context size: Not more than 20k recommended - coherency may degrade.
Chat Template: ChatML; Metharme/Pygmalion (as per UnslopNemo) may work, but effects are untested
Samplers: A Temperature-Last of 1 and Min-P of 0.1 are viable, but haven't been finetuned. Activate DRY if repetition appears. XTC is untested.

Quantization

I am working on v2, as such I won't bother with quantizations. Try my other models!

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: MarinaraSpaghetti/NemoMix-Unleashed-12B
  - model: TheDrummer/UnslopNemo-12B-v4.1
base_model: TheDrummer/UnslopNemo-12B-v4.1
merge_method: slerp
dtype: bfloat16
tokenizer_source: "MarinaraSpaghetti/NemoMix-Unleashed-12B"
chat_template: "chatml"
parameters:
  t: [0.2, 0.7, 0.9, 0.8, 0.3]

Downloads last month: 3

Safetensors

Model size

12B params

Tensor type

BF16

Model tree for redrix/matricide-12B-Unslop-Unleashed

MarinaraSpaghetti/NemoMix-Unleashed-12B

TheDrummer/UnslopNemo-12B-v4.1

Merge model

this model

Quantizations

2 models