Instructions to use gabrielemidulla/LPI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gabrielemidulla/LPI with Transformers:

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

pipe = pipeline("text-generation", model="gabrielemidulla/LPI")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gabrielemidulla/LPI")
model = AutoModelForCausalLM.from_pretrained("gabrielemidulla/LPI", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use gabrielemidulla/LPI with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/gabrielemidulla/LPI

SGLang

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

Docker Model Runner
How to use gabrielemidulla/LPI with Docker Model Runner:
```
docker model run hf.co/gabrielemidulla/LPI
```

gabrielemidulla commited on Aug 21, 2025

Commit

6fc76f1

verified ·

1 Parent(s): edf4374

Model save

Browse files

Files changed (3) hide show

model.safetensors +1 -1
runs/Aug21_21-56-47_gabri/events.out.tfevents.1755806212.gabri.39435.3 +3 -0
training_args.bin +1 -1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:93115fb5fe237da47c41d6271115605331e686c8b8541d2a6050038b89ec87c1
 size 536223056

 version https://git-lfs.github.com/spec/v1
+oid sha256:50a90d1f68f044ef60a4eadac1dc07060cfafe8cafb16fdba39c7b10b150e259
 size 536223056

runs/Aug21_21-56-47_gabri/events.out.tfevents.1755806212.gabri.39435.3 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:194572e04dd68f69afe5dc97fadc025f02244d39565c93f547ded3857bd2a4a7
+size 32705

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8d55d4fa697fffa432c406da3dc3ef272c128d055d1be75b1696d0754deb949a
 size 6161

 version https://git-lfs.github.com/spec/v1
+oid sha256:bdbb94489bd8d57e64836ea08d56e78b9f5248f6a43029e686a107679df7ba79
 size 6161