Text Generation
Transformers
Safetensors
Portuguese
qwen3
text-generation-inference
conversational
Eval Results (legacy)
Instructions to use Polygl0t/Tucano2-qwen-0.5B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Polygl0t/Tucano2-qwen-0.5B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Polygl0t/Tucano2-qwen-0.5B-Instruct") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Polygl0t/Tucano2-qwen-0.5B-Instruct") model = AutoModelForMultimodalLM.from_pretrained("Polygl0t/Tucano2-qwen-0.5B-Instruct") 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 Settings
- vLLM
How to use Polygl0t/Tucano2-qwen-0.5B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Polygl0t/Tucano2-qwen-0.5B-Instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Polygl0t/Tucano2-qwen-0.5B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Polygl0t/Tucano2-qwen-0.5B-Instruct
- SGLang
How to use Polygl0t/Tucano2-qwen-0.5B-Instruct 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 "Polygl0t/Tucano2-qwen-0.5B-Instruct" \ --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": "Polygl0t/Tucano2-qwen-0.5B-Instruct", "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 "Polygl0t/Tucano2-qwen-0.5B-Instruct" \ --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": "Polygl0t/Tucano2-qwen-0.5B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Polygl0t/Tucano2-qwen-0.5B-Instruct with Docker Model Runner:
docker model run hf.co/Polygl0t/Tucano2-qwen-0.5B-Instruct
| { | |
| "add_bos_token": false, | |
| "add_eos_token": false, | |
| "add_prefix_space": null, | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<|unk|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1": { | |
| "content": "<|im_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "<|im_end|>", | |
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| "content": "<tool_response>", | |
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| "content": "</tool_response>", | |
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| "content": "<|fim_suffix|>", | |
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| "49124": { | |
| "content": "<|fim_middle|>", | |
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| "49125": { | |
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| "49126": { | |
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| }, | |
| "49127": { | |
| "content": "<|image_pad|>", | |
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| "single_word": false, | |
| "special": false | |
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| "49128": { | |
| "content": "<|image_placeholder|>", | |
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| } | |
| }, | |
| "bos_token": "<|im_start|>", | |
| "bos_token_id": 1, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "eos_token_id": 2, | |
| "extra_special_tokens": {}, | |
| "legacy": false, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 4096, | |
| "pad_token": "<|pad|>", | |
| "pad_token_id": 49109, | |
| "padding_side": "right", | |
| "sp_model_kwargs": {}, | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "truncation_side": "right", | |
| "unk_token": "<|unk|>", | |
| "unk_token_id": 0, | |
| "use_default_system_prompt": false | |
| } | |