Instructions to use tencent/Tencent-Hunyuan-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/Tencent-Hunyuan-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tencent/Tencent-Hunyuan-Large")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tencent/Tencent-Hunyuan-Large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use tencent/Tencent-Hunyuan-Large with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tencent/Tencent-Hunyuan-Large" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tencent/Tencent-Hunyuan-Large", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tencent/Tencent-Hunyuan-Large
- SGLang
How to use tencent/Tencent-Hunyuan-Large 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 "tencent/Tencent-Hunyuan-Large" \ --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": "tencent/Tencent-Hunyuan-Large", "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 "tencent/Tencent-Hunyuan-Large" \ --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": "tencent/Tencent-Hunyuan-Large", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tencent/Tencent-Hunyuan-Large with Docker Model Runner:
docker model run hf.co/tencent/Tencent-Hunyuan-Large
| { | |
| "added_tokens_decoder": {}, | |
| "additional_special_tokens": [ | |
| "<|startoftext|>", | |
| "<|extra_0|>", | |
| "<|extra_4|>", | |
| "<|extra_5|>", | |
| "<|eos|>" | |
| ], | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_hy.HYTokenizer", | |
| null | |
| ] | |
| }, | |
| "bos_token": "<|startoftext|>", | |
| "chat_template": "{% set context = {'has_head': true} %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = message['content'] %}{% if loop.index0 == 0 %}{% if content == '' %}{% set _ = context.update({'has_head': false}) %}{% else %}{% set content = '<|startoftext|>' + content + '<|extra_4|>' %}{% endif %}{% endif %}{% if message['role'] == 'user' %}{% if loop.index0 == 1 and not context.has_head %}{% set content = '<|startoftext|>' + content %}{% endif %}{% if loop.index0 == 1 and context.has_head %}{% set content = content + '<|extra_0|>' %}{% else %}{% set content = '<|startoftext|>' + content + '<|extra_0|>' %}{% endif %}{% elif message['role'] == 'assistant' %}{% set content = content + '<|eos|>' %}{% endif %}{{ content }}{% endfor %}", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 1048576, | |
| "pad_token": "<|pad|>", | |
| "tokenizer_class": "HYTokenizer" | |
| } | |