Text Generation
Transformers
Safetensors
t5
text2text-generation
biology
single-cell
single-cell analysis
text-generation-inference
Instructions to use zjunlp/chatcell-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zjunlp/chatcell-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zjunlp/chatcell-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zjunlp/chatcell-base") model = AutoModelForSeq2SeqLM.from_pretrained("zjunlp/chatcell-base") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use zjunlp/chatcell-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zjunlp/chatcell-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zjunlp/chatcell-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/zjunlp/chatcell-base
- SGLang
How to use zjunlp/chatcell-base 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/chatcell-base" \ --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/chatcell-base", "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/chatcell-base" \ --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/chatcell-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use zjunlp/chatcell-base with Docker Model Runner:
docker model run hf.co/zjunlp/chatcell-base
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The project <b>ChatCell</b>
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aims to facilitate single-cell analysis with natural language, which derives from the <a href="https://github.com/vandijklab/cell2sentence-ft">Cell2Sentence</a>
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technique to obtain cell language tokens and utilizes cell vocabulary adaptation for T5-based pre-training.
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<a href="https://chat.openai.com/g/g-vUwj222gQ-chatcell">💻GPTStore App</a>.
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</div>
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The project <b>ChatCell</b>
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aims to facilitate single-cell analysis with natural language, which derives from the <a href="https://github.com/vandijklab/cell2sentence-ft">Cell2Sentence</a>
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technique to obtain cell language tokens and utilizes cell vocabulary adaptation for T5-based pre-training. Have a try with the demo at
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<a href="https://chat.openai.com/g/g-vUwj222gQ-chatcell">💻GPTStore App</a>.
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