How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MrRobotoAI/X3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MrRobotoAI/X3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/MrRobotoAI/X3
Quick Links

merge

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

Merge Details

Merge Method

This model was merged using the Linear 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: MrRobotoAI/Nord-v1.2-8b-Uncensored-BASE-128k+svjack/Genshin_Impact_aya_23_8B_v3_Plot_Chat_roleplay_chat_lora_small
  - model: MrRobotoAI/Nord-v1.2-8b-Uncensored-BASE-128k+svjack/DPO_Genshin_Impact_Mistral_Plot_Engine_Step_Json_Short_lora_small
  - model: MrRobotoAI/Nord-v1.2-8b-Uncensored-BASE-128k+svjack/Genshin_Impact_Mistral_v3_Plot_Chat_roleplay_chat_lora_small
  - model: MrRobotoAI/Nord-v1.2-8b-Uncensored-BASE-128k+multimodalai/talent-critique-llama3_1_8b-tt_lora-model_4_2k-adapter-rev_3
parameters:
    weight: 1.0
merge_method: linear
normalize: true
dtype: float16
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Model size
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Tensor type
F16
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