Instructions to use Xtra-Computing/XtraGPT-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Xtra-Computing/XtraGPT-14B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Xtra-Computing/XtraGPT-14B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Xtra-Computing/XtraGPT-14B", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Xtra-Computing/XtraGPT-14B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Xtra-Computing/XtraGPT-14B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Xtra-Computing/XtraGPT-14B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Xtra-Computing/XtraGPT-14B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Xtra-Computing/XtraGPT-14B

SGLang

How to use Xtra-Computing/XtraGPT-14B 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-14B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Xtra-Computing/XtraGPT-14B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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-14B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Xtra-Computing/XtraGPT-14B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Xtra-Computing/XtraGPT-14B with Docker Model Runner:
```
docker model run hf.co/Xtra-Computing/XtraGPT-14B
```

nuojohnchen commited on 28 days ago

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@@ -177,13 +177,12 @@ For more details on the license terms, please visit [ModelGo.li](https://www.mod
 If you use XtraGPT in your research, please cite our paper:
 ```
-@misc{chen2025xtragpt,
-      title={XtraGPT: Context-Aware and Controllable Academic Paper Revision for Human-AI Collaboration},
-      author={Nuo Chen and Andre Lin HuiKai and Jiaying Wu and Junyi Hou and Zining Zhang and Qian Wang and Xidong Wang and Bingsheng He},
-      year={2025},
-      eprint={2505.11336},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL},
-      url={https://arxiv.org/abs/2505.11336},
 }
 ```

 If you use XtraGPT in your research, please cite our paper:
 ```
+@inproceedings{
+chen2026xtragpt,
+title={XtraGPT: Context-Aware and Controllable Academic Paper Revision via Human-AI Collaboration},
+author={Nuo Chen and Andre Lin HuiKai and Jiaying Wu and Junyi Hou and Zining Zhang and Qian Wang and Xidong Wang and Bingsheng He},
+booktitle = "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+year={2026},
+note={Available on arXiv:2505.11336}
 }
 ```