Feature Extraction
PEFT
Safetensors
English
medical
clinical
biomedical
retrieval
embeddings
sentence-similarity
dense-retriever
llm2vec
lora
from-scratch
qwen3
KOS-V5
university-of-kentucky
university-of-louisville
ccts
Instructions to use Kentucky-Open-Science/KOS-V5-Retriever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Kentucky-Open-Science/KOS-V5-Retriever with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Kentucky-Open-Science/KOS-V5-Instruct") model = PeftModel.from_pretrained(base_model, "Kentucky-Open-Science/KOS-V5-Retriever") - Notebooks
- Google Colab
- Kaggle
Download meta.json from Kentucky-Open-Science/KOS-V5-Retriever: direct link, hf CLI and curl.
- Browser
- Download file 108 Bytes
-
https://huggingface.co/Kentucky-Open-Science/KOS-V5-Retriever/resolve/main/meta.json
- Command line
-
hf download hf://Kentucky-Open-Science/KOS-V5-Retriever/meta.json
-
curl -L -o meta.json https://huggingface.co/Kentucky-Open-Science/KOS-V5-Retriever/resolve/main/meta.json
108 Bytes
| {"base": "/project/ibi-staff/LLM_TEXT/sft/models/011_legT_step40", "bidirectional": true, "pooling": "mean"} |