How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pot99rta/OmegaPatricide-12B-DarkerDirective-Mell"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pot99rta/OmegaPatricide-12B-DarkerDirective-Mell",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/pot99rta/OmegaPatricide-12B-DarkerDirective-Mell
Quick Links

OmegaPatricide-12B-DarkerDirective-Mell

image/png Go Dark.. Unleash Yourself..

merge

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

Use ChatML or Mistral for preset.

Merge Details

Merge Method

This model was merged using the TIES merge method using redrix/patricide-12B-Unslop-Mell as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: redrix/patricide-12B-Unslop-Mell
    #no parameters necessary for base model
  - model: redrix/patricide-12B-Unslop-Mell
    parameters:
      density: 0.5
      weight: 0.5
  - model: ReadyArt/Omega-Darker_The-Final-Directive-12B
    parameters:
      density: 0.5
      weight: 0.5

merge_method: ties
base_model: redrix/patricide-12B-Unslop-Mell
parameters:
  normalize: false
  int8_mask: true
dtype: float16
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Safetensors
Model size
12B params
Tensor type
F16
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