Instructions to use Unbabel/Tower-Plus-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Unbabel/Tower-Plus-2B with Transformers:

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

pipe = pipeline("text-generation", model="Unbabel/Tower-Plus-2B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Unbabel/Tower-Plus-2B")
model = AutoModelForCausalLM.from_pretrained("Unbabel/Tower-Plus-2B")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Unbabel/Tower-Plus-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Unbabel/Tower-Plus-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Unbabel/Tower-Plus-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Unbabel/Tower-Plus-2B

SGLang

How to use Unbabel/Tower-Plus-2B 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 "Unbabel/Tower-Plus-2B" \
    --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": "Unbabel/Tower-Plus-2B",
		"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 "Unbabel/Tower-Plus-2B" \
        --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": "Unbabel/Tower-Plus-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Unbabel/Tower-Plus-2B with Docker Model Runner:
```
docker model run hf.co/Unbabel/Tower-Plus-2B
```

Improve model card: Add pipeline tag, paper, and project page links

by nielsr HF Staff - opened Jul 2, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

-1

Files changed (1) hide show

README.md +6 -1

README.md CHANGED Viewed

@@ -1,6 +1,5 @@
 ---
 base_model: google/gemma-2-2B
-license: cc-by-nc-sa-4.0
 language:
 - de
 - nl
@@ -25,8 +24,14 @@ language:
 - ro
 - fi
 library_name: transformers
 ---
 ![Tower Plus Pareto](./Tower-plus-pareto.png)
 # Model Description:

 ---
 base_model: google/gemma-2-2B
 language:
 - de
 - nl
 - ro
 - fi
 library_name: transformers
+license: cc-by-nc-sa-4.0
+pipeline_tag: text-generation
 ---
+This repository contains the model presented in the paper [Tower+: Bridging Generality and Translation Specialization in Multilingual LLMs](https://huggingface.co/papers/2506.17080).
+You can find the official project page and other related models in the [Unbabel Tower+ Collection](https://huggingface.co/collections/Unbabel/tower-plus-6846ca452a10c0905dc03c0f).
 ![Tower Plus Pareto](./Tower-plus-pareto.png)
 # Model Description: