Instructions to use darkc0de/XortronCriminalComputingConfig with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use darkc0de/XortronCriminalComputingConfig with Transformers:

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

pipe = pipeline("text-generation", model="darkc0de/XortronCriminalComputingConfig")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("darkc0de/XortronCriminalComputingConfig")
model = AutoModelForCausalLM.from_pretrained("darkc0de/XortronCriminalComputingConfig")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use darkc0de/XortronCriminalComputingConfig with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "darkc0de/XortronCriminalComputingConfig"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "darkc0de/XortronCriminalComputingConfig",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/darkc0de/XortronCriminalComputingConfig

SGLang

How to use darkc0de/XortronCriminalComputingConfig 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 "darkc0de/XortronCriminalComputingConfig" \
    --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": "darkc0de/XortronCriminalComputingConfig",
		"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 "darkc0de/XortronCriminalComputingConfig" \
        --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": "darkc0de/XortronCriminalComputingConfig",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use darkc0de/XortronCriminalComputingConfig with Docker Model Runner:
```
docker model run hf.co/darkc0de/XortronCriminalComputingConfig
```

darkc0de commited on Jun 24, 2025

Commit

85fb3a6

verified ·

1 Parent(s): b33c4c2

Update README.md

Browse files

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README.md +3 -36

README.md CHANGED Viewed

@@ -16,7 +16,9 @@ pipeline_tag: text-generation
 ---
 You can try this model now for free at [xortron.tech](https://xortron.tech/)
-![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6540a02d1389943fef4d2640/IrOYjlLQ2QR18w9lGWWxe.jpeg)wledgeable, and of course state-of-the-art **Uncensored** performance.
 Please use **responsibly**, or at least **discretely**.
@@ -25,38 +27,3 @@ This model will help you do anything and everything you probably shouldn't be do
 As of this writing, this model tops the **UGI Leaderboard** for models under 70 billion parameters in both the **UGI** and **W10** categories.
 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6540a02d1389943fef4d2640/_proSyYDP1-HxfHC3fc-Q.jpeg)
-# merge
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
-## Merge Details
-### Merge Method
-This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [darkc0de/XortronCriminalComputing](https://huggingface.co/darkc0de/XortronCriminalComputing) as a base.
-### Models Merged
-The following models were included in the merge:
-* [TroyDoesAI/BlackSheep-24B](https://huggingface.co/TroyDoesAI/BlackSheep-24B)
-* [darkc0de/XortronCriminalComputing](https://huggingface.co/darkc0de/XortronCriminalComputing)
-### Configuration
-The following YAML configuration was used to produce this model:
-```yaml
-models:
-  - model: darkc0de/XortronCriminalComputing
-  - model: TroyDoesAI/BlackSheep-24B
-    parameters:
-      density: 0.8
-      weight: 0.8
-merge_method: ties
-base_model: darkc0de/XortronCriminalComputing
-dtype: float16
-```

 ---
 You can try this model now for free at [xortron.tech](https://xortron.tech/)
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6540a02d1389943fef4d2640/IrOYjlLQ2QR18w9lGWWxe.jpeg)
+State-of-the-art **Uncensored** performance.
 Please use **responsibly**, or at least **discretely**.
 As of this writing, this model tops the **UGI Leaderboard** for models under 70 billion parameters in both the **UGI** and **W10** categories.
 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6540a02d1389943fef4d2640/_proSyYDP1-HxfHC3fc-Q.jpeg)