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
报错Exception: data did not match any variant of untagged enum PyPreTokenizerTypeWrapper at line 78 column 3
#4
by leedahae340 - opened
用例子代码加载的时候,报错
可以尝试使用tokenizers==0.15.2版本
underspirit changed discussion status to closed
ImportError: tokenizers>=0.19,<0.20 is required for a normal functioning of this module, but found tokenizers==0.15.2.
transformer导入又出现问题。
ImportError: tokenizers>=0.19,<0.20 is required for a normal functioning of this module, but found tokenizers==0.15.2.
transformer导入又出现问题。
pip install transformers==4.38.1解决,