Instructions to use BAAI/AquilaChat2-7B-16K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/AquilaChat2-7B-16K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BAAI/AquilaChat2-7B-16K", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("BAAI/AquilaChat2-7B-16K", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use BAAI/AquilaChat2-7B-16K with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BAAI/AquilaChat2-7B-16K" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BAAI/AquilaChat2-7B-16K", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/BAAI/AquilaChat2-7B-16K
- SGLang
How to use BAAI/AquilaChat2-7B-16K 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 "BAAI/AquilaChat2-7B-16K" \ --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": "BAAI/AquilaChat2-7B-16K", "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 "BAAI/AquilaChat2-7B-16K" \ --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": "BAAI/AquilaChat2-7B-16K", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use BAAI/AquilaChat2-7B-16K with Docker Model Runner:
docker model run hf.co/BAAI/AquilaChat2-7B-16K
| license: other | |
|  | |
| <h4 align="center"> | |
| <p> | |
| <b>English</b> | | |
| <a href="https://huggingface.co/BAAI/AquilaChat2-7B-16K/blob/main/README_zh.md">简体中文</a> | |
| </p> | |
| </h4> | |
| We opensource our **Aquila2** series, now including **Aquila2**, the base language models, namely **Aquila2-7B** and **Aquila2-34B**, as well as **AquilaChat2**, the chat models, namely **AquilaChat2-7B** and **AquilaChat2-34B**, as well as the long-text chat models, namely **AquilaChat2-7B-16k** and **AquilaChat2-34B-16k** | |
| The additional details of the Aquila model will be presented in the official technical report. Please stay tuned for updates on official channels. | |
| ## Quick Start AquilaChat2-7B-16K(Chat model) | |
| ### 1. Inference | |
| ```python | |
| import torch | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| from transformers import BitsAndBytesConfig | |
| device = torch.device("cuda:0") | |
| model_info = "BAAI/AquilaChat2-7B-16K" | |
| tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True) | |
| quantization_config=BitsAndBytesConfig( | |
| load_in_4bit=True, | |
| bnb_4bit_use_double_quant=True, | |
| bnb_4bit_quant_type="nf4", | |
| bnb_4bit_compute_dtype=torch.bfloat16, | |
| ) | |
| model = AutoModelForCausalLM.from_pretrained(model_info, trust_remote_code=True, torch_dtype=torch.float16, | |
| # quantization_config=quantization_config, # Uncomment this line for 4bit quantization | |
| ) | |
| model.eval() | |
| model.to(device) | |
| text = "请给出10个要到北京旅游的理由。" | |
| from predict import predict | |
| out = predict(model, text, tokenizer=tokenizer, max_gen_len=200, top_p=0.95, | |
| seed=1234, topk=100, temperature=0.9, sft=True, device=device, | |
| model_name="AquilaChat2-7B-16K") | |
| print(out) | |
| ``` | |
| ## License | |
| Aquila2 series open-source model is licensed under [ BAAI Aquila Model Licence Agreement](https://huggingface.co/BAAI/AquilaChat2-7B-16K/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf) |