Instructions to use VerbACxSS/sempl-it-sentence-reorganizer-bnb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use VerbACxSS/sempl-it-sentence-reorganizer-bnb with Transformers:

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

pipe = pipeline("text-generation", model="VerbACxSS/sempl-it-sentence-reorganizer-bnb")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("VerbACxSS/sempl-it-sentence-reorganizer-bnb", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use VerbACxSS/sempl-it-sentence-reorganizer-bnb with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/VerbACxSS/sempl-it-sentence-reorganizer-bnb

SGLang

How to use VerbACxSS/sempl-it-sentence-reorganizer-bnb 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 "VerbACxSS/sempl-it-sentence-reorganizer-bnb" \
    --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": "VerbACxSS/sempl-it-sentence-reorganizer-bnb",
		"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 "VerbACxSS/sempl-it-sentence-reorganizer-bnb" \
        --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": "VerbACxSS/sempl-it-sentence-reorganizer-bnb",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use VerbACxSS/sempl-it-sentence-reorganizer-bnb with Docker Model Runner:
```
docker model run hf.co/VerbACxSS/sempl-it-sentence-reorganizer-bnb
```

RedHitMark commited on Apr 15, 2025

Commit

8e3f8ff

verified ·

1 Parent(s): ce282c3

Update README.md

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@@ -9,6 +9,27 @@ library_name: transformers
 tags:
 - legal
 ---
 ## Usage
 Install the following dependencies:
 ```sh
@@ -57,8 +78,8 @@ Load SEMPL-IT model and tokenizer:
 ```py
 from transformers import AutoModelForCausalLM, AutoTokenizer
-tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-sentence-reorganizer-awq")
-model = AutoModelForCausalLM.from_pretrained("VerbACxSS/sempl-it-sentence-reorganizer-awq").to("cuda")
 ```
 Define and apply chat template:

 tags:
 - legal
 ---
+# sempl-it-sentence-reorganizer-bnb
+SEMPL-IT aims to simplify Italian administrative texts using a progressive approach based on multiple specialized models.
+Each model addresses a specific aspect of the text transformation process, ensuring a step-by-step refinement.
+## Simplification Pipeline
+The complete text simplification pipeline follows eight sequential steps:
+1. [proofreading](https://huggingface.co/VerbACxSS/sempl-it-proofreading-bnb)
+2. [lex](https://huggingface.co/VerbACxSS/sempl-it-lex-bnb)
+3. [connectives](https://huggingface.co/VerbACxSS/sempl-it-connectives-bnb)
+4. [expressions](https://huggingface.co/VerbACxSS/sempl-it-expressions-bnb)
+5. [sentence-splitter](https://huggingface.co/VerbACxSS/sempl-it-sentence-splitter-bnb)
+6. [nominalizations](https://huggingface.co/VerbACxSS/sempl-it-nominalizations-bnb)
+7. [verbs](https://huggingface.co/VerbACxSS/sempl-it-verbs-bnb)
+8. [sentence-reorganizer](https://huggingface.co/VerbACxSS/sempl-it-sentence-reorganizer-bnb)  (this)
+## Web App
+To integrate this model into the full system, check out:
+- Frontend: [GitHub Repository](https://github.com/VerbACxSS/sempl-it-frontend)
+- Backend: [GitHub Repository](https://github.com/VerbACxSS/sempl-it-backend)
+- Inference: [GitHub Repository](https://github.com/VerbACxSS/sempl-it-inference)
 ## Usage
 Install the following dependencies:
 ```sh
 ```py
 from transformers import AutoModelForCausalLM, AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-sentence-reorganizer-bnb")
+model = AutoModelForCausalLM.from_pretrained("VerbACxSS/sempl-it-sentence-reorganizer-bnb").to("cuda")
 ```
 Define and apply chat template: