Instructions to use MatterWaveAI/grt-30m-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MatterWaveAI/grt-30m-chat with Transformers:

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

pipe = pipeline("text-generation", model="MatterWaveAI/grt-30m-chat")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("MatterWaveAI/grt-30m-chat", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MatterWaveAI/grt-30m-chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MatterWaveAI/grt-30m-chat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MatterWaveAI/grt-30m-chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/MatterWaveAI/grt-30m-chat

SGLang

How to use MatterWaveAI/grt-30m-chat 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 "MatterWaveAI/grt-30m-chat" \
    --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": "MatterWaveAI/grt-30m-chat",
		"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 "MatterWaveAI/grt-30m-chat" \
        --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": "MatterWaveAI/grt-30m-chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use MatterWaveAI/grt-30m-chat with Docker Model Runner:
```
docker model run hf.co/MatterWaveAI/grt-30m-chat
```

davidhouseholter commited on about 12 hours ago

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@@ -2,7 +2,7 @@ f0aa0fd5bbba646dc7ae058d9e7e3436e4b2c1f8c422a2bfc06c8de09de076fc  chat_template.
 c2b264a05e11914a8e41c1610f3c81e15d38151c459a1c66caaaa0381d804685  config.json
 4638cae59268889fb9731e481655c2da3a756f35d6d733f6e052ab76ba71b051  eval_results.json
 da90aebf9dbd74d88711c9cc69becf4b4d0e14d0f2f677d1351f4c48982bb23b  generation_config.json
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 be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506  tokenizer.json

 c2b264a05e11914a8e41c1610f3c81e15d38151c459a1c66caaaa0381d804685  config.json
 4638cae59268889fb9731e481655c2da3a756f35d6d733f6e052ab76ba71b051  eval_results.json
 da90aebf9dbd74d88711c9cc69becf4b4d0e14d0f2f677d1351f4c48982bb23b  generation_config.json
+a3ed909af07bc2bd42fc35c475492684ef05e963f3f5a136b3bad86e8e531982  GRT_Whitepaper.pdf
 ee613803cb7b2c618def7e6c79476e1aab4e887cc08e234204b6bad12ad772bc  model.safetensors
 ecb06a27215a3c961a49f94e8293b8c4493dbc802b15e36925e019a41d114ead  README.md
 be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506  tokenizer.json