Text Generation
Transformers
Safetensors
English
hunyuan_v1_dense
python
code-generation
code-assistant
causal-lm
full-finetune
hunyuan
instruct
conversational
Instructions to use 11-47/Hunyuan-PythonGOD-0.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 11-47/Hunyuan-PythonGOD-0.5B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="11-47/Hunyuan-PythonGOD-0.5B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("11-47/Hunyuan-PythonGOD-0.5B") model = AutoModelForCausalLM.from_pretrained("11-47/Hunyuan-PythonGOD-0.5B") 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]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 11-47/Hunyuan-PythonGOD-0.5B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "11-47/Hunyuan-PythonGOD-0.5B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "11-47/Hunyuan-PythonGOD-0.5B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/11-47/Hunyuan-PythonGOD-0.5B
- SGLang
How to use 11-47/Hunyuan-PythonGOD-0.5B 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 "11-47/Hunyuan-PythonGOD-0.5B" \ --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": "11-47/Hunyuan-PythonGOD-0.5B", "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 "11-47/Hunyuan-PythonGOD-0.5B" \ --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": "11-47/Hunyuan-PythonGOD-0.5B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use 11-47/Hunyuan-PythonGOD-0.5B with Docker Model Runner:
docker model run hf.co/11-47/Hunyuan-PythonGOD-0.5B
| {%- if not add_generation_prompt is defined %} | |
| {%- set add_generation_prompt = false %} | |
| {%- endif %} | |
| {%- set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='', is_first_sp=true, is_first_user=true, is_last_user=false) %} | |
| {%- for message in messages %} | |
| {%- if message['role'] == 'system' %} | |
| {%- if ns.is_first_sp %} | |
| {%- set ns.system_prompt = ns.system_prompt + message['content'] %} | |
| {%- set ns.is_first_sp = false %} | |
| {%- else %} | |
| {% set ns.system_prompt = ns.system_prompt + ' | |
| ' + message['content'] %} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {{- bos_token }} | |
| {{- ns.system_prompt }} | |
| {%- if tools %} | |
| {%- if ns.system_prompt != '' %} | |
| {{- ' | |
| # Tools | |
| You may call one or more functions to assist with the user query.' }} | |
| {%- else %} | |
| {{- '# Tools | |
| You may call one or more functions to assist with the user query.' }} | |
| {%- endif %} | |
| {{- ' | |
| You are provided with function signatures within <tools></tools> XML tags:' }} | |
| {{- ' | |
| <tools> | |
| ' }} | |
| {%- for tool in tools %} | |
| {%- if loop.index0 > 1 %} | |
| {{- ' | |
| ' }} | |
| {%- endif %} | |
| {{- tool | tojson }} | |
| {%- endfor %} | |
| {{- ' | |
| </tools> | |
| ' }} | |
| {{- 'For function call returns, you should first print <tool_calls>' }} | |
| {{- 'For each function call, you should return object like: | |
| ' }} | |
| {{- '<tool_call>function_name | |
| ```json | |
| function_arguments_in_json_format | |
| ```</tool_call>' }} | |
| {{- 'At the end of function call returns, you should print </tool_calls>' }} | |
| {%- endif %} | |
| {%- if ns.system_prompt != '' or tools %} | |
| {{- '<|hy_place▁holder▁no▁3|>' }} | |
| {%- endif %} | |
| {%- for message in messages %} | |
| {%- if message['role'] == 'user' %} | |
| {%- set ns.is_tool = false %} | |
| {%- set ns.is_first = false %} | |
| {%- set ns.is_last_user = true %} | |
| {{- '<|hy_User|>' + message['content'] + '<|hy_Assistant|>' }} | |
| {%- endif %} | |
| {%- if message['role'] == 'assistant' and message['tool_calls'] is defined and message['tool_calls'] is not none %} | |
| {%- set ns.is_last_user = false %} | |
| {%- if ns.is_tool %} | |
| {{- '</tool_responses>' + '<|hy_Assistant|>' }} | |
| {%- endif %} | |
| {%- set ns.is_first = false %} | |
| {%- set ns.is_tool = false %} | |
| {%- set ns.is_output_first = true %} | |
| {%- for tool in message['tool_calls'] %} | |
| {%- set arguments = tool['function']['arguments'] %} | |
| {%- if arguments is not string %} | |
| {%- set arguments = arguments | tojson %} | |
| {%- endif %} | |
| {%- if not ns.is_first %} | |
| {%- if message['content'] is none %} | |
| {{- '<tool_calls><tool_call>' + tool['function']['name'] + ' | |
| ' + '```json' + ' | |
| ' + arguments + ' | |
| ' + '```' + '</tool_call>' }} | |
| {%- else %} | |
| {{- message['content'] + '<tool_calls><tool_call>' + tool['function']['name'] + ' | |
| ' + '```json' + ' | |
| ' + arguments + ' | |
| ' + '```' + '</tool_call>' }} | |
| {%- endif %} | |
| {%- set ns.is_first = true %} | |
| {%- else %} | |
| {{- ' | |
| ' + '<tool_call>' + tool['function']['name'] + ' | |
| ' + '```json' + ' | |
| ' + arguments + ' | |
| ' + '```' + '</tool_call>' }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {{- '</tool_calls>' + eos_token }} | |
| {%- endif %} | |
| {%- if message['role'] == 'assistant' and (message['tool_calls'] is not defined or message['tool_calls'] is none) %} | |
| {%- set content = message['content'] %} | |
| {%- if '<answer>' in content and not loop.last %} | |
| {%- set content = content.split('<answer>')[-1].strip('</answer>').strip() %} | |
| {%- endif %} | |
| {%- set ns.is_last_user = false %} | |
| {%- if ns.is_tool %} | |
| {{- '</tool_responses>' + '<|hy_Assistant|>' + content + eos_token }} | |
| {%- set ns.is_tool = false %} | |
| {%- else %} | |
| {{- content + eos_token }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- if message['role'] == 'tool' %} | |
| {%- set ns.is_last_user = false %} | |
| {%- set ns.is_tool = true %} | |
| {%- if ns.is_output_first %} | |
| {{- '<|hy_User|>' + '<tool_responses><tool_response>' + message['content'] + '</tool_response>' }} | |
| {%- set ns.is_output_first = false %} | |
| {%- else %} | |
| {{- ' | |
| <tool_response>' + message['content'] + '</tool_response>' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if ns.is_tool %} | |
| {{- '</tool_responses>' + '<|hy_Assistant|>' }} | |
| {%- endif %} | |
| {%- if add_generation_prompt and not ns.is_last_user and not ns.is_tool %} | |
| {{- '<|hy_Assistant|>' }} | |
| {%- endif %} | |
| {%- if enable_thinking is defined and not enable_thinking %} | |
| {{- '<think> | |
| </think> | |
| ' }} | |
| {%- endif %} |