Instructions to use InstaDeepAI/ChatNT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/ChatNT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="InstaDeepAI/ChatNT", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InstaDeepAI/ChatNT", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use InstaDeepAI/ChatNT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "InstaDeepAI/ChatNT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "InstaDeepAI/ChatNT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/InstaDeepAI/ChatNT
- SGLang
How to use InstaDeepAI/ChatNT 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 "InstaDeepAI/ChatNT" \ --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": "InstaDeepAI/ChatNT", "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 "InstaDeepAI/ChatNT" \ --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": "InstaDeepAI/ChatNT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use InstaDeepAI/ChatNT with Docker Model Runner:
docker model run hf.co/InstaDeepAI/ChatNT
Update README.md
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README.md
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outputs use the LLaMA tokenizer, augmented with `<DNA>` as a special token to mark sequence insertion points.
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### Limitations and Disclaimer
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ChatNT can only handle questions related to the 27 tasks it has been trained on. ChatNT is **not** a clinical or diagnostic tool.
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It can produce incorrect or “hallucinated” answers, particularly on out‑of‑distribution inputs, and its numeric predictions may suffer digit‑level errors. Confidence
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estimates require post‑hoc calibration. Users should always validate critical outputs against experiments or specialized bioinformatics
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pipelines.
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outputs use the LLaMA tokenizer, augmented with `<DNA>` as a special token to mark sequence insertion points.
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### Limitations and Disclaimer
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ChatNT can only handle questions related to the 27 tasks it has been trained on, including the same format of DNA sequences. ChatNT is **not** a clinical or diagnostic tool.
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| 50 |
It can produce incorrect or “hallucinated” answers, particularly on out‑of‑distribution inputs, and its numeric predictions may suffer digit‑level errors. Confidence
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| 51 |
estimates require post‑hoc calibration. Users should always validate critical outputs against experiments or specialized bioinformatics
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pipelines.
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