Instructions to use zjunlp/zhixi-13b-diff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zjunlp/zhixi-13b-diff with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zjunlp/zhixi-13b-diff")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zjunlp/zhixi-13b-diff") model = AutoModelForCausalLM.from_pretrained("zjunlp/zhixi-13b-diff") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zjunlp/zhixi-13b-diff with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zjunlp/zhixi-13b-diff" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zjunlp/zhixi-13b-diff", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/zjunlp/zhixi-13b-diff
- SGLang
How to use zjunlp/zhixi-13b-diff 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 "zjunlp/zhixi-13b-diff" \ --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": "zjunlp/zhixi-13b-diff", "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 "zjunlp/zhixi-13b-diff" \ --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": "zjunlp/zhixi-13b-diff", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use zjunlp/zhixi-13b-diff with Docker Model Runner:
docker model run hf.co/zjunlp/zhixi-13b-diff
Update README.md
Browse files
README.md
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@@ -46,6 +46,9 @@ All weights have been uploaded to HuggingFace🤗. It should be noted that all t
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- \[**June 2023**\] The project name has been changed from CaMA to KnowLM.
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- \[**June 2023**\] Release the first version of pre-trained weights and the LoRA weights.
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## Contents
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- [Cases](#1)
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- \[**June 2023**\] The project name has been changed from CaMA to KnowLM.
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- \[**June 2023**\] Release the first version of pre-trained weights and the LoRA weights.
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## Why it's called ZhiXi (智析)?
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In Chinese, "Zhi" (智) signifies intelligence, referencing the AI's advanced language understanding capabilities. "Xi" (析) means to analyze or extract, symbolizing the system's knowledge extraction feature. Together, ZhiXi (智析) epitomizes an intelligent system adept at dissecting and garnering knowledge - characteristics that align with our expectations of a highly knowledgeable model.
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## Contents
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- [Cases](#1)
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