Text Generation
Transformers
Safetensors
English
qwen3
medical
clinical
biomedical
radiology
from-scratch
base-model
university-of-kentucky
university-of-louisville
ccts
text-generation-inference
Instructions to use Kentucky-Open-Science/KOS-V5-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kentucky-Open-Science/KOS-V5-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Kentucky-Open-Science/KOS-V5-Base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Kentucky-Open-Science/KOS-V5-Base") model = AutoModelForCausalLM.from_pretrained("Kentucky-Open-Science/KOS-V5-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Kentucky-Open-Science/KOS-V5-Base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Kentucky-Open-Science/KOS-V5-Base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Kentucky-Open-Science/KOS-V5-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Kentucky-Open-Science/KOS-V5-Base
- SGLang
How to use Kentucky-Open-Science/KOS-V5-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 "Kentucky-Open-Science/KOS-V5-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": "Kentucky-Open-Science/KOS-V5-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 "Kentucky-Open-Science/KOS-V5-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": "Kentucky-Open-Science/KOS-V5-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Kentucky-Open-Science/KOS-V5-Base with Docker Model Runner:
docker model run hf.co/Kentucky-Open-Science/KOS-V5-Base
Model card: UK CoM/CCTS attribution in structured metadata; win/loss by quartile; comparator roster; drop step count
Browse files
README.md
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- en
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library_name: transformers
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pipeline_tag: text-generation
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developed_by: University of Kentucky College of Medicine
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model_name: KOS-V5-Base
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model_codename: Catbird
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model_type: qwen3
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- base-model
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- qwen3
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- university-of-kentucky
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- ccts
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---
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# KOS-V5-Base · *"Catbird"*
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**Developed by
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**A 3.72B-parameter medical language model trained from scratch** — not distilled, not pruned, not
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continued-pretrained from a general base. KOS-V5 (codename **Catbird**) is the fifth-generation
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## Attribution
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## Citation
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title = {KOS-V5-Base (Catbird): a from-scratch 3.72B medical language model},
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author = {Kentucky Open Science},
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year = {2026},
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note = {University of Kentucky College of Medicine
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Center for Clinical and Translational Science
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url = {https://huggingface.co/Kentucky-Open-Science/KOS-V5-Base}
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}
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```
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- en
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library_name: transformers
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pipeline_tag: text-generation
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developed_by: University of Kentucky (College of Medicine Office for Research; Center for Clinical and Translational Science) and University of Louisville (Kentucky Center for Digital Innovation)
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affiliations:
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- name: University of Kentucky — College of Medicine, Office for Research
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url: https://medicine.uky.edu/sites/research
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- name: University of Kentucky — Center for Clinical and Translational Science (CCTS)
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url: https://www.ccts.uky.edu/
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- name: University of Louisville — Kentucky Center for Digital Innovation
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url: https://centers.louisville.edu/kentucky-center-digital-innovation
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model_name: KOS-V5-Base
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model_codename: Catbird
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model_type: qwen3
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- base-model
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- qwen3
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- university-of-kentucky
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- university-of-louisville
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- ccts
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---
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# KOS-V5-Base · *"Catbird"*
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**Developed by**
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**University of Kentucky**
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- [College of Medicine, Office for Research](https://medicine.uky.edu/sites/research)
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- [Center for Clinical and Translational Science (CCTS)](https://www.ccts.uky.edu/)
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**University of Louisville**
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- [Kentucky Center for Digital Innovation](https://centers.louisville.edu/kentucky-center-digital-innovation)
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**A 3.72B-parameter medical language model trained from scratch** — not distilled, not pruned, not
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continued-pretrained from a general base. KOS-V5 (codename **Catbird**) is the fifth-generation
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## Attribution
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**University of Kentucky**
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- [College of Medicine, Office for Research](https://medicine.uky.edu/sites/research)
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- [Center for Clinical and Translational Science (CCTS)](https://www.ccts.uky.edu/)
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**University of Louisville**
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- [Kentucky Center for Digital Innovation](https://centers.louisville.edu/kentucky-center-digital-innovation)
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## Citation
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title = {KOS-V5-Base (Catbird): a from-scratch 3.72B medical language model},
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author = {Kentucky Open Science},
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year = {2026},
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note = {University of Kentucky (College of Medicine Office for Research;
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Center for Clinical and Translational Science) and
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University of Louisville (Kentucky Center for Digital Innovation)},
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url = {https://huggingface.co/Kentucky-Open-Science/KOS-V5-Base}
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}
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```
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