Instructions to use Unbabel/Tower-Plus-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Unbabel/Tower-Plus-2B") model = AutoModelForCausalLM.from_pretrained("Unbabel/Tower-Plus-2B", 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
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Verified signatureThis PR improves the model card for the `Unbabel/Tower-Plus-2B` model by: - Adding the `pipeline_tag: text-generation` to the metadata, which enhances discoverability on the Hugging Face Hub (e.g., at https://huggingface.co/models?pipeline_tag=text-generation). - Including a direct link to the research paper "[Tower+: Bridging Generality and Translation Specialization in Multilingual LLMs](https://huggingface.co/papers/2506.17080)", providing users with easy access to its technical details and findings. - Adding a link to the official project page ([Unbabel Tower+ Collection](https://huggingface.co/collections/Unbabel/tower-plus-6846ca452a10c0905dc03c0f)), offering further context and related resources for the Tower+ models.10b4606
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