Text Generation
Transformers
PyTorch
JAX
Safetensors
Portuguese
llama
text-generation-inference
Eval Results (legacy)
Instructions to use TucanoBR/Tucano-2b4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TucanoBR/Tucano-2b4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TucanoBR/Tucano-2b4")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("TucanoBR/Tucano-2b4") model = AutoModelForMultimodalLM.from_pretrained("TucanoBR/Tucano-2b4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TucanoBR/Tucano-2b4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TucanoBR/Tucano-2b4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TucanoBR/Tucano-2b4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TucanoBR/Tucano-2b4
- SGLang
How to use TucanoBR/Tucano-2b4 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 "TucanoBR/Tucano-2b4" \ --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": "TucanoBR/Tucano-2b4", "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 "TucanoBR/Tucano-2b4" \ --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": "TucanoBR/Tucano-2b4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TucanoBR/Tucano-2b4 with Docker Model Runner:
docker model run hf.co/TucanoBR/Tucano-2b4
| { | |
| "results": { | |
| "arc_pt": { | |
| "acc": 0.26666666666666666, | |
| "acc_stderr": 0.012933850109759568, | |
| "acc_norm": 0.30256410256410254, | |
| "acc_norm_stderr": 0.013435492568854205 | |
| }, | |
| "hellaswag_pt": { | |
| "acc": 0.37772239679271863, | |
| "acc_stderr": 0.005046899546439457, | |
| "acc_norm": 0.47014844511864773, | |
| "acc_norm_stderr": 0.00519566110400487 | |
| }, | |
| "truthfulqa_pt": { | |
| "mc1": 0.24111675126903553, | |
| "mc1_stderr": 0.015248032494426427, | |
| "mc2": 0.3911004265246538, | |
| "mc2_stderr": 0.014560723432804852 | |
| } | |
| }, | |
| "versions": { | |
| "arc_pt": 0, | |
| "hellaswag_pt": 1, | |
| "truthfulqa_pt": 1 | |
| }, | |
| "config": { | |
| "model": "hf-auto", | |
| "model_args": "pretrained=/lustre/mlnvme/data/asen_hpc-mula/checkpoints-llama/slurm_job_17049106/step_1960000", | |
| "batch_size": 1, | |
| "device": "cuda:0", | |
| "no_cache": false, | |
| "limit": null, | |
| "bootstrap_iters": 100000, | |
| "description_dict": {} | |
| } | |
| } |