Instructions to use xverse/XVERSE-13B-256K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xverse/XVERSE-13B-256K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="xverse/XVERSE-13B-256K", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("xverse/XVERSE-13B-256K", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use xverse/XVERSE-13B-256K with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "xverse/XVERSE-13B-256K" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "xverse/XVERSE-13B-256K", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/xverse/XVERSE-13B-256K
- SGLang
How to use xverse/XVERSE-13B-256K 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 "xverse/XVERSE-13B-256K" \ --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": "xverse/XVERSE-13B-256K", "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 "xverse/XVERSE-13B-256K" \ --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": "xverse/XVERSE-13B-256K", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use xverse/XVERSE-13B-256K with Docker Model Runner:
docker model run hf.co/xverse/XVERSE-13B-256K
pom commited on
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update
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README.md
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For all the comparison models mentioned above, we prioritize the disclosure of their officially published results. In the absence of official data, we refer to the results derived from our own evaluation pipline.
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### Loading with Transformers
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cpm_kernels>=1.0.11
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xformers
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可通过以下代码加载 XVERSE-13B-256K 模型进行对话:
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For all the comparison models mentioned above, we prioritize the disclosure of their officially published results. In the absence of official data, we refer to the results derived from our own evaluation pipline.
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### Loading with Transformers
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环境安装:
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Environment Setup:
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pip install -r requirements.txt
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可通过以下代码加载 XVERSE-13B-256K 模型进行对话:
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requirements.txt
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transformers==4.31.0
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torch>=2.0
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gradio>=3.39.0
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accelerate>=0.21.0
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cpm_kernels>=1.0.11
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xformers
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