Instructions to use ICONNAI/ICONN-e1-Beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ICONNAI/ICONN-e1-Beta with Transformers:

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

pipe = pipeline("text-generation", model="ICONNAI/ICONN-e1-Beta")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ICONNAI/ICONN-e1-Beta")
model = AutoModelForCausalLM.from_pretrained("ICONNAI/ICONN-e1-Beta", 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 ICONNAI/ICONN-e1-Beta with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ICONNAI/ICONN-e1-Beta"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ICONNAI/ICONN-e1-Beta",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ICONNAI/ICONN-e1-Beta

SGLang

How to use ICONNAI/ICONN-e1-Beta 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 "ICONNAI/ICONN-e1-Beta" \
    --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": "ICONNAI/ICONN-e1-Beta",
		"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 "ICONNAI/ICONN-e1-Beta" \
        --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": "ICONNAI/ICONN-e1-Beta",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ICONNAI/ICONN-e1-Beta with Docker Model Runner:
```
docker model run hf.co/ICONNAI/ICONN-e1-Beta
```

Enderchef commited on Jun 24, 2025

Commit

de15a59

verified ·

1 Parent(s): ca41146

Update README.md

Browse files

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README.md +17 -0

README.md CHANGED Viewed

@@ -151,4 +151,21 @@ def run_iconn_chatbot(model_name="ICONNAI/ICONN-e1"):
 if __name__ == "__main__":
     run_iconn_chatbot()
 ```

 if __name__ == "__main__":
     run_iconn_chatbot()
+```
+## Cite Us
+**If you use ICONN 1, please cite us as follows:**
+```DoI
+@misc{iconnai_2025,
+	author       = { ICONNAI },
+	title        = { ICONN-e1-Beta (Revision ca41146) },
+	year         = 2025,
+	url          = { https://huggingface.co/ICONNAI/ICONN-e1-Beta },
+	doi          = { 10.57967/hf/5861 },
+	publisher    = { Hugging Face }
+}
 ```