How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dark-pen/apodex-1.0-2B-SFT-rebased"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dark-pen/apodex-1.0-2B-SFT-rebased",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'
Use Docker
docker model run hf.co/dark-pen/apodex-1.0-2B-SFT-rebased
Quick Links

apodex-1.0-2B-SFT-rebased

apodex-1.0-2B-SFT-rebased is a merge of the following models using LazyMergekit:

🧩 Configuration

models:
  - model: Qwen/Qwen3.5-2B-Base
  - model: apodex/Apodex-1.0-2B-SFT
merge_method: arcee_fusion
base_model: Qwen/Qwen3.5-2B-Base
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "dark-pen/apodex-1.0-2B-SFT-rebased"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,

    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
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