Instructions to use Unbabel/Tower-Plus-72B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Unbabel/Tower-Plus-72B with Transformers:

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

pipe = pipeline("text-generation", model="Unbabel/Tower-Plus-72B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Unbabel/Tower-Plus-72B")
model = AutoModelForCausalLM.from_pretrained("Unbabel/Tower-Plus-72B")
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-72B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Unbabel/Tower-Plus-72B"
# 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-72B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Unbabel/Tower-Plus-72B

SGLang

How to use Unbabel/Tower-Plus-72B 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-72B" \
    --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-72B",
		"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-72B" \
        --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-72B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Unbabel/Tower-Plus-72B with Docker Model Runner:
```
docker model run hf.co/Unbabel/Tower-Plus-72B
```

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/1

Discussion Files changed

+13

-8

nielsr

Jul 2, 2025

This PR improves the model card for the Tower+ 72B model.
It adds the pipeline_tag: text-generation to the metadata, which ensures the model is properly categorized and discoverable on the Hugging Face Hub (e.g., at https://huggingface.co/models?pipeline_tag=text-generation).
It also adds prominent links to the paper and the project page at the beginning of the model card for easier access to relevant information.

Improve model card: Add pipeline tag, paper and project page linksb7d70253

jmprcp

Jul 2, 2025

•

edited Jul 2, 2025

Hi! Can you remove the changes on the prompt example please? We prefer to present them with the newlines written explicitly. This applies to the changes you made on the repositories of our other models. Thanks!

Update README.md4e7eb0a9

nielsr

Jul 4, 2025

Thanks, applied it!

farajian changed pull request status to merged Jul 24, 2025

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