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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<h2 id="3">🧬 Single-cell Analysis Tasks</h2>
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- <b>Random Cell Sentence Generation.</b>
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Random cell sentence generation challenges the model to create cell sentences devoid of predefined biological conditions or constraints. This task aims to evaluate the model's ability to generate valid and contextually appropriate cell sentences, potentially simulating natural variations in cellular behavior.
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<h2 id="3">🧬 Single-cell Analysis Tasks</h2>
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ChatCell can handle the following single-cell tasks:
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- <b>Random Cell Sentence Generation.</b>
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Random cell sentence generation challenges the model to create cell sentences devoid of predefined biological conditions or constraints. This task aims to evaluate the model's ability to generate valid and contextually appropriate cell sentences, potentially simulating natural variations in cellular behavior.
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