Text Classification
Transformers
Safetensors
English
Chinese
qwen3_5
image-text-to-text
decision-model
system-one
biomedical
clinical-trials
pharmacovigilance
regulatory
genomics
llm-as-a-judge
calibration
jev
typed-decisions
calibrated-probabilities
Eval Results (legacy)
Instructions to use lighteternal/biodecision-v2-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lighteternal/biodecision-v2-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lighteternal/biodecision-v2-4b")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("lighteternal/biodecision-v2-4b") model = AutoModelForMultimodalLM.from_pretrained("lighteternal/biodecision-v2-4b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download v1_to_v2.png from lighteternal/biodecision-v2-4b: direct link, hf CLI and curl.
- Browser
- Download file 116 kB
-
https://huggingface.co/lighteternal/biodecision-v2-4b/resolve/main/v1_to_v2.png
- Command line
-
hf download hf://lighteternal/biodecision-v2-4b/v1_to_v2.png
-
curl -L -o v1_to_v2.png https://huggingface.co/lighteternal/biodecision-v2-4b/resolve/main/v1_to_v2.png
116 kB

- Xet hash:
- 53a4eb8de3ecbb0dc630690099505ec26105959bf8cfed10fea206f310d5ae6c
- Size of remote file:
- 116 kB
- SHA256:
- da38953114561b48dfce8f57cb913316d47f85236cfd8e80d9baad9a8a184980
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