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 17 days ago

Commit

0cbd325

verified ·

1 Parent(s): 389abf4

Update configuration_lightning.py

Browse files

Files changed (1) hide show

configuration_lightning.py +4 -0

configuration_lightning.py CHANGED Viewed

@@ -13,10 +13,14 @@ class LightningConfig(PretrainedConfig):
         num_layers=4,
         dropout=0.1,
         max_seq_len=160,
         **kwargs
     ):
         super().__init__(
             tie_word_embeddings=False,
             **kwargs
         )

         num_layers=4,
         dropout=0.1,
         max_seq_len=160,
+        pad_token_id=0,
+        eos_token_id=2,
         **kwargs
     ):
         super().__init__(
             tie_word_embeddings=False,
+            pad_token_id=pad_token_id,
+            eos_token_id=eos_token_id,
             **kwargs
         )