Instructions to use m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA with Transformers:

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

pipe = pipeline("text-generation", model="m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA

SGLang

How to use m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA 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 "m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA with Docker Model Runner:
```
docker model run hf.co/m-polignano/ANITA-NEXT-24B-Magistral-2506-ITA
```

ANITA-NEXT-24B-Magistral-2506-ITA

File size: 2,358 Bytes

---
license: apache-2.0
language:
- en
- it
base_model:
- mistralai/Magistral-Small-2506
pipeline_tag: text-generation
library_name: transformers
tags:
- ita
- italian
- anita
- magistral
- 24b
- uniba
- bari
- italy
- italia
- Conversational
- LLaMantino
---

<img src="https://cdn-lfs-us-1.hf.co/repos/6a/53/6a53c7003eb58616a925d670ab49c9a64e28595f5374cfd9f06de3c443fd2733/edda28e12f8bd6701b6cc6c0f21f95a65fca2c7848e8968a721a33b8d547ddeb?response-content-disposition=inline%3B+filename*%3DUTF-8%27%27Anita-Next_full.png%3B+filename%3D%22Anita-Next_full.png%22%3B&response-content-type=image%2Fpng&Expires=1754915206&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTc1NDkxNTIwNn19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy11cy0xLmhmLmNvL3JlcG9zLzZhLzUzLzZhNTNjNzAwM2ViNTg2MTZhOTI1ZDY3MGFiNDljOWE2NGUyODU5NWY1Mzc0Y2ZkOWYwNmRlM2M0NDNmZDI3MzMvZWRkYTI4ZTEyZjhiZDY3MDFiNmNjNmMwZjIxZjk1YTY1ZmNhMmM3ODQ4ZTg5NjhhNzIxYTMzYjhkNTQ3ZGRlYj9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPSoifV19&Signature=Efty9m3kbArTanxoJiaEiR6WvM-T%7EvxIO9A-NEm177kGSRzQczV89VIa%7EMWRBzevCxDRrgv2q7RLQAeUk3Z9bfah3iuwTuv4q6Ls3SD9M3B3W9MfzRDZtSS2Xejxn0d9nHP172baE8QnbRPt8xd79lE-Y8Zjz3vG5DqECCf9UWTnKAJiK44JsbvkErWg7a08RqmTPnXg1HDdSKd3bhFWp2OOg5f4TXyHN6vbAPF0rRBsWuQg5cXOHjrLSnNnGkUJytn%7EyvnMTQhfgl3i4mNlIM4hGKb5dD1ZniOh1o35b5zmN2zq9h3iv4t2MQuiEWW2UGIfdOtXARLjk5du%7EnJgCQ__&Key-Pair-Id=K24J24Z295AEI9" alt="anita_next" border="0" width="400px">
<hr>
<!--<img src="https://i.ibb.co/6mHSRm3/llamantino53.jpg" width="200"/>-->
<h3><i>"Built on <b>mistral/Magistral-Small-2506</b>"</i></i></h3>
<p style="text-align:justify;"><b>NITA-NEXT-24B-Magistral-2506-ITA</b> is a model of the <a href="https://huggingface.co/swap-uniba"><b>ANITA</b></a> - <i>Large Language Models family</i>.
The model is a fine-tuned version of <a href="https://huggingface.co/mistralai/Magistral-Small-2506"><b>Magistral-Small-2506</b></a> (a fine-tuned <b>Magistral model</b>).
This model version aims to be the a <b>Multilingual Model</b> 🏁  (EN 🇺🇸 + ITA🇮🇹) to further fine-tuning on Specific Tasks in Italian.</p>


The 🌟**ANITA project**🌟 *(**A**dvanced **N**atural-based interaction for the **ITA**lian language)*
wants to provide Italian NLP researchers with an improved model for the Italian Language 🇮🇹 use cases.

<hr>