Instructions to use SUSTech/SUS-Chat-72B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SUSTech/SUS-Chat-72B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SUSTech/SUS-Chat-72B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SUSTech/SUS-Chat-72B") model = AutoModelForCausalLM.from_pretrained("SUSTech/SUS-Chat-72B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SUSTech/SUS-Chat-72B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SUSTech/SUS-Chat-72B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SUSTech/SUS-Chat-72B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SUSTech/SUS-Chat-72B
- SGLang
How to use SUSTech/SUS-Chat-72B 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 "SUSTech/SUS-Chat-72B" \ --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": "SUSTech/SUS-Chat-72B", "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 "SUSTech/SUS-Chat-72B" \ --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": "SUSTech/SUS-Chat-72B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SUSTech/SUS-Chat-72B with Docker Model Runner:
docker model run hf.co/SUSTech/SUS-Chat-72B
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Download README.md from SUSTech/SUS-Chat-72B: direct link, hf CLI and curl.
- Browser
- Download file 4.77 kB
-
https://huggingface.co/SUSTech/SUS-Chat-72B/resolve/main/README.md
- Command line
-
hf download hf://SUSTech/SUS-Chat-72B/README.md
-
curl -L -o README.md https://huggingface.co/SUSTech/SUS-Chat-72B/resolve/main/README.md
4.77 kB
metadata
license: other
🐷SUS-Chat: Instruction tuning done right
not currently in use中文 | English
🐷SUS-Chat: Instruction tuning done right
中文 | English
News
2023-12-09: 🔥
Tigerbotvariant has been deleted,SUS-Chat-34Bis now the the top-ranked LLaMA model and the top-ranked chat model.2023-12-07: SUS-Chat-34B is now available on WiseModel🧠.
2023-12-06: Try SUS-Chat-34B chat-ui.
2023-12-05: SUS-Chat-34B is now available on ModelScope🤖
2023-12-05: SUS-Chat-34B is ranked 2nd in Open LLM leaderboard and surpassed all models under 70B.
2023-12-01: SUS-Chat-34B is now available on HuggingFace🤗.