Instructions to use zjunlp/MolGen-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zjunlp/MolGen-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zjunlp/MolGen-7b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zjunlp/MolGen-7b") model = AutoModelForCausalLM.from_pretrained("zjunlp/MolGen-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zjunlp/MolGen-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zjunlp/MolGen-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zjunlp/MolGen-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/zjunlp/MolGen-7b
- SGLang
How to use zjunlp/MolGen-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 "zjunlp/MolGen-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": "zjunlp/MolGen-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 "zjunlp/MolGen-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": "zjunlp/MolGen-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use zjunlp/MolGen-7b with Docker Model Runner:
docker model run hf.co/zjunlp/MolGen-7b
Yin Fang commited on
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README.md
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## 📚 Citation
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If you use our repository, please cite:
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```bibtex
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@
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author = {Yin Fang and
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Ningyu Zhang and
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Zhuo Chen and
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Xiaohui Fan and
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Huajun Chen},
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title = {Domain-Agnostic Molecular Generation with Self-feedback},
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year = {
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}
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```
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## 📚 Citation
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If you use our repository, please cite:
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```bibtex
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@inproceedings{fang2023domain,
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author = {Yin Fang and
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Ningyu Zhang and
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Zhuo Chen and
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Xiaohui Fan and
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Huajun Chen},
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title = {Domain-Agnostic Molecular Generation with Self-feedback},
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booktitle = {{ICLR}},
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publisher = {OpenReview.net},
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year = {2024},
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url = {https://openreview.net/pdf?id=9rPyHyjfwP}
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}
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```
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