Instructions to use wxjiao/ParroT-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wxjiao/ParroT-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="wxjiao/ParroT-7b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("wxjiao/ParroT-7b") model = AutoModelForCausalLM.from_pretrained("wxjiao/ParroT-7b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use wxjiao/ParroT-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "wxjiao/ParroT-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wxjiao/ParroT-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/wxjiao/ParroT-7b
- SGLang
How to use wxjiao/ParroT-7b 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 "wxjiao/ParroT-7b" \ --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": "wxjiao/ParroT-7b", "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 "wxjiao/ParroT-7b" \ --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": "wxjiao/ParroT-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use wxjiao/ParroT-7b with Docker Model Runner:
docker model run hf.co/wxjiao/ParroT-7b
How to write the prompt to translate for this model?
#1
by xianf - opened
My prompt is like "Translate this sentence from English to German: ", but it does not work.
Hi, currently please follow the prompt used for training. We provide the inference code here: https://github.com/wxjiao/ParroT/blob/master/train/inference.py, where you can find the prompt format.
Basically, the prompt looks like below:
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
We are translating the following sentences from Chinese to English.
### Input:
检查情况显示,市场销售的粮油、肉类、水果、蔬菜、蛋奶等生活必需品供应充足,商品价格基本稳定,未发现严重违法违规行为,市场经营秩序总体平稳。
### Response: