Text Classification
PEFT
Safetensors
English
decision-model
calibration
lora
multiple-choice
typesafe
qwen3.5
Eval Results (legacy)
Instructions to use jaredpalmer/kev-0.8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jaredpalmer/kev-0.8b with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3.5-0.8B-Base") model = PeftModel.from_pretrained(base_model, "jaredpalmer/kev-0.8b") - Notebooks
- Google Colab
- Kaggle
calibration built in: head.pt carries the fitted temperature; KEV_TEMPERATURE=1.0 for raw logits
54f4f87 verified Download head.pt from jaredpalmer/kev-0.8b: direct link, hf CLI and curl.
- Browser
- Download file 2.1 MB
-
https://huggingface.co/jaredpalmer/kev-0.8b/resolve/54f4f8777356cd5bbbb6c6919c657f26e6f2f6d8/head.pt
- Command line
-
hf download hf://jaredpalmer/kev-0.8b@54f4f8777356cd5bbbb6c6919c657f26e6f2f6d8/head.pt
-
curl -L -o head.pt https://huggingface.co/jaredpalmer/kev-0.8b/resolve/54f4f8777356cd5bbbb6c6919c657f26e6f2f6d8/head.pt
2.1 MB
- Xet hash:
- b54eeea26fcb7ee135599c78ac275bd75f599edda1d0dcf579fcd134557f2565
- Size of remote file:
- 2.1 MB
- SHA256:
- 39f4343ccccc65e583bbfff0de0e11bfedb849fcfaaf94b50ac4f2b73bc79c65
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