Instructions to use Xtra-Computing/XtraGPT-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xtra-Computing/XtraGPT-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Xtra-Computing/XtraGPT-7B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Xtra-Computing/XtraGPT-7B", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Xtra-Computing/XtraGPT-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Xtra-Computing/XtraGPT-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Xtra-Computing/XtraGPT-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Xtra-Computing/XtraGPT-7B
- SGLang
How to use Xtra-Computing/XtraGPT-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 "Xtra-Computing/XtraGPT-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": "Xtra-Computing/XtraGPT-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 "Xtra-Computing/XtraGPT-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": "Xtra-Computing/XtraGPT-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Xtra-Computing/XtraGPT-7B with Docker Model Runner:
docker model run hf.co/Xtra-Computing/XtraGPT-7B
Improve language tag
Browse filesHi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.
README.md
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---
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license: other
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license_name: mg0-2.0
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license_link: https://github.com/Xtra-Computing/ModelGo/blob/main/MG_licenses/V2/MG0-2.0.txt
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language:
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```
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---
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license: other
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license_name: mg0-2.0
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license_link: https://github.com/Xtra-Computing/ModelGo/blob/main/MG_licenses/V2/MG0-2.0.txt
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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pipeline_tag: text-generation
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- chat
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library_name: transformers
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---
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```
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@misc{XtraGPT,
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title = {XtraGPT},
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url = {https://huggingface.co/Xtra-Computing/XtraGPT-7B},
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author = {Nuo Chen, Andre Lin HuiKai, Junyi Hou, Zining Zhang, Qian Wang, Xidong Wang, Bingsheng He},
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month = {March},
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year = {2025}
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}
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```
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