Instructions to use ThingAI/Dwarf-15M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ThingAI/Dwarf-15M with Transformers:

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

pipe = pipeline("text-generation", model="ThingAI/Dwarf-15M", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("ThingAI/Dwarf-15M", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ThingAI/Dwarf-15M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ThingAI/Dwarf-15M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ThingAI/Dwarf-15M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ThingAI/Dwarf-15M

SGLang

How to use ThingAI/Dwarf-15M 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 "ThingAI/Dwarf-15M" \
    --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": "ThingAI/Dwarf-15M",
		"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 "ThingAI/Dwarf-15M" \
        --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": "ThingAI/Dwarf-15M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ThingAI/Dwarf-15M with Docker Model Runner:
```
docker model run hf.co/ThingAI/Dwarf-15M
```

Dwarf-15M

File size: 618 Bytes

{
  "architectures": [
    "DwarfForCausalLM"
  ],
  "model_type": "dwarf",
  "auto_map": {
    "AutoConfig": "configuration_dwarf.DwarfConfig",
    "AutoModelForCausalLM": "modeling_dwarf.DwarfForCausalLM"
  },
  "vocab_size": 8202,
  "d_model": 320,
  "n_layers": 12,
  "n_heads": 5,
  "n_kv_heads": 1,
  "d_ff": 864,
  "max_seq_len": 2048,
  "rope_theta": 10000.0,
  "norm_eps": 1e-05,
  "head_dim": 64,
  "torch_dtype": "float32",
  "transformers_version": "4.45.0",
  "bos_token_id": 1,
  "eos_token_id": 2,
  "num_hidden_layers": 12,
  "hidden_size": 320,
  "num_attention_heads": 5,
  "num_key_value_heads": 1
}