Text Generation
GGUF
How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "QuantFactory/Blue-Orchid-2x7b-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "QuantFactory/Blue-Orchid-2x7b-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/QuantFactory/Blue-Orchid-2x7b-GGUF:
Quick Links

QuantFactory/Blue-Orchid-2x7b-GGUF

This is quantized version of nakodanei/Blue-Orchid-2x7b created using llama.cpp

Model Description

Roleplaying focused MoE Mistral model.

One expert is a merge of mostly RP models, the other is a merge of mostly storywriting models. So it should be good at both. The base model is SanjiWatsuki/Kunoichi-DPO-v2-7B.

  • Expert 1 is a merge of LimaRP, Limamono, Noromaid 0.4 DPO and good-robot.
  • Expert 2 is a merge of Erebus, Holodeck, Dans-AdventurousWinds-Mk2, Opus, Ashhwriter and good-robot.

Prompt template (LimaRP):

### Instruction:
{system prompt}

### Input:
User: {prompt}

### Response:
Character: 

Alpaca prompt template should work fine too.

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GGUF
Model size
13B params
Architecture
llama
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