Text Generation
Transformers
PyTorch
Safetensors
English
i3
conversational
efficient
i3-architecture
custom_code
Instructions to use i3-lab/i3-12m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use i3-lab/i3-12m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="i3-lab/i3-12m", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("i3-lab/i3-12m", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use i3-lab/i3-12m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "i3-lab/i3-12m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "i3-lab/i3-12m", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/i3-lab/i3-12m
- SGLang
How to use i3-lab/i3-12m 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 "i3-lab/i3-12m" \ --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": "i3-lab/i3-12m", "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 "i3-lab/i3-12m" \ --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": "i3-lab/i3-12m", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use i3-lab/i3-12m with Docker Model Runner:
docker model run hf.co/i3-lab/i3-12m
Update README.md
Browse files
README.md
CHANGED
|
@@ -27,6 +27,7 @@ The **i3 Model** is a memory-optimized language model designed for conversationa
|
|
| 27 |
- **Max Sequence Length**: 256
|
| 28 |
- **Total Parameters**: 12,691,186
|
| 29 |
- **Tokenization**: Memory-efficient variable-length chunking (2-3 characters)
|
|
|
|
| 30 |
|
| 31 |

|
| 32 |
|
|
|
|
| 27 |
- **Max Sequence Length**: 256
|
| 28 |
- **Total Parameters**: 12,691,186
|
| 29 |
- **Tokenization**: Memory-efficient variable-length chunking (2-3 characters)
|
| 30 |
+
- **Total tokens**: 334,524,736
|
| 31 |
|
| 32 |

|
| 33 |
|