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 Settings
- 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
Add EvalEval community eval results
#23
by EvalEvalBot - opened
.eval_results/mmlu_pro.yaml
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
- dataset:
|
| 2 |
+
id: TIGER-Lab/MMLU-Pro
|
| 3 |
+
task_id: mmlu_pro
|
| 4 |
+
source:
|
| 5 |
+
name: EvalEval
|
| 6 |
+
url: https://huggingface.co/datasets/evaleval/EEE_datastore/blob/192329fb7d6b15b7b0936a1a58ae862aa7e8ba24/flat/objects/5c/9f/5c9f18ed-3247-4af2-b44f-2a504735554b.json
|
| 7 |
+
value: 60.2
|