Instructions to use SUSTech/SUS-Chat-34B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SUSTech/SUS-Chat-34B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SUSTech/SUS-Chat-34B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SUSTech/SUS-Chat-34B") model = AutoModelForCausalLM.from_pretrained("SUSTech/SUS-Chat-34B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SUSTech/SUS-Chat-34B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SUSTech/SUS-Chat-34B" # 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-34B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SUSTech/SUS-Chat-34B
- SGLang
How to use SUSTech/SUS-Chat-34B 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-34B" \ --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-34B", "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-34B" \ --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-34B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SUSTech/SUS-Chat-34B with Docker Model Runner:
docker model run hf.co/SUSTech/SUS-Chat-34B
Upload README.md with huggingface_hub
Browse files
README.md
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# News
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- 2023-12-09: 🔥 `Tigerbot` variant has been
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[deleted](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/438),
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`SUS-Chat-34B` is now the the top-ranked LLaMA model and the
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# News
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- 2024-1-04: 🔥 `cloudyu` created a series of top ranked
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[MOE](cloudyu/Yi-34Bx2-MoE-60B) based on our model
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- 2023-12-09: 🔥 `Tigerbot` variant has been
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[deleted](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/438),
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`SUS-Chat-34B` is now the the top-ranked LLaMA model and the
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