Instructions to use GreatCaptainNemo/ProLLaMA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GreatCaptainNemo/ProLLaMA with Transformers:

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

pipe = pipeline("text-generation", model="GreatCaptainNemo/ProLLaMA")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("GreatCaptainNemo/ProLLaMA")
model = AutoModelForCausalLM.from_pretrained("GreatCaptainNemo/ProLLaMA")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use GreatCaptainNemo/ProLLaMA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GreatCaptainNemo/ProLLaMA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GreatCaptainNemo/ProLLaMA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/GreatCaptainNemo/ProLLaMA

SGLang

How to use GreatCaptainNemo/ProLLaMA 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 "GreatCaptainNemo/ProLLaMA" \
    --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": "GreatCaptainNemo/ProLLaMA",
		"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 "GreatCaptainNemo/ProLLaMA" \
        --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": "GreatCaptainNemo/ProLLaMA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use GreatCaptainNemo/ProLLaMA with Docker Model Runner:
```
docker model run hf.co/GreatCaptainNemo/ProLLaMA
```

GreatCaptainNemo commited on Sep 4, 2025

Commit

c7adc64

verified ·

1 Parent(s): 7c873bf

Update README.md

Browse files

Files changed (1) hide show

README.md +5 -4

README.md CHANGED Viewed

@@ -132,10 +132,11 @@ if __name__ == '__main__':
 # Citation:
 ```
-@article{lv2024prollama,
-  title={ProLLaMA: A Protein Large Language Model for Multi-Task Protein Language Processing},
   author={Lv, Liuzhenghao and Lin, Zongying and Li, Hao and Liu, Yuyang and Cui, Jiaxi and Chen, Calvin Yu-Chian and Yuan, Li and Tian, Yonghong},
-  journal={arXiv preprint arXiv:2402.16445},
-  year={2024}
 }
 ```

 # Citation:
 ```
+@article{lv2025prollama,
+  title={Prollama: A protein large language model for multi-task protein language processing},
   author={Lv, Liuzhenghao and Lin, Zongying and Li, Hao and Liu, Yuyang and Cui, Jiaxi and Chen, Calvin Yu-Chian and Yuan, Li and Tian, Yonghong},
+  journal={IEEE Transactions on Artificial Intelligence},
+  year={2025},
+  publisher={IEEE}
 }
 ```