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

Libraries

How to use ACATECH/ncos with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ACATECH/ncos")
model = AutoModelForCausalLM.from_pretrained("ACATECH/ncos", device_map="auto")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ACATECH/ncos with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/ACATECH/ncos

SGLang

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

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

usernameisokaynow commited on May 1, 2025

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@@ -97,7 +97,7 @@ The resulting 4bit version of the model is roughly 40GB in size. The model can r
 In addition to running the model in gradio, as sketched above, you can also deploy on-premise using the ollama-library (version: v0.6.7). After setting up a ollama-"modelfile" according to your use case (e.g. the preferred system prompt and some additional setups can be found in the config files of the model) you can add the model to ollama like this:
 ```
-ollama create ncos-q40 -f ./ncos-gguf/Modelfile
 ```

 In addition to running the model in gradio, as sketched above, you can also deploy on-premise using the ollama-library (version: v0.6.7). After setting up a ollama-"modelfile" according to your use case (e.g. the preferred system prompt and some additional setups can be found in the config files of the model) you can add the model to ollama like this:
 ```
+ollama create ncos-q4_0 -f ./ncos-gguf/Modelfile
 ```