Instructions to use Aobangaming/lightning-30m-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Aobangaming/lightning-30m-ft with Transformers:

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

pipe = pipeline("text-generation", model="Aobangaming/lightning-30m-ft", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Aobangaming/lightning-30m-ft", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Aobangaming/lightning-30m-ft with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Aobangaming/lightning-30m-ft

SGLang

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

Docker Model Runner
How to use Aobangaming/lightning-30m-ft with Docker Model Runner:
```
docker model run hf.co/Aobangaming/lightning-30m-ft
```

Aobangaming commited on 19 days ago

Commit

389abf4

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1 Parent(s): f8f9c68

Update README.md

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@@ -94,13 +94,14 @@ input_ids = torch.tensor([encoded.ids])
 outputs = model.generate(
     input_ids,
     max_new_tokens=100,
     temperature=0.8,
     top_k=40,
     top_p=0.6
 )
 print(tokenizer.decode(outputs[0].tolist()))
 ```
 ## Training Details

 outputs = model.generate(
     input_ids,
     max_new_tokens=100,
+    do_sample=True,
     temperature=0.8,
     top_k=40,
     top_p=0.6
 )
 print(tokenizer.decode(outputs[0].tolist()))
 ```
 ## Training Details