Instructions to use Aobangaming/lightning-105m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Aobangaming/lightning-105m with Transformers:

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

pipe = pipeline("text-generation", model="Aobangaming/lightning-105m", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Aobangaming/lightning-105m", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Aobangaming/lightning-105m with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Aobangaming/lightning-105m"
# 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-105m",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Aobangaming/lightning-105m

SGLang

How to use Aobangaming/lightning-105m 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-105m" \
    --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-105m",
		"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-105m" \
        --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-105m",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Aobangaming/lightning-105m with Docker Model Runner:
```
docker model run hf.co/Aobangaming/lightning-105m
```

Aobangaming commited on Sep 20

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@@ -32,13 +32,13 @@ a larger size and weight.
 - **Model type:** Transformer
 - **Language(s) (NLP):** English
 - **License:** MIT
-- **Finetuned from model [optional]:** Aoban-2.7-L
-### Model Sources [optional]
 <!-- Provide the basic links for the model. -->
-- **Repository:** https://huggingface.co/Aobangaming/lightning-60m
 ## Uses

 - **Model type:** Transformer
 - **Language(s) (NLP):** English
 - **License:** MIT
+- **Finetuned from model :** lightning-30m
+### Model Sources
 <!-- Provide the basic links for the model. -->
+- **Repository:** https://huggingface.co/Aobangaming/lightning-105m
 ## Uses