Text Classification
PEFT
Safetensors
English
decision-model
calibration
lora
multiple-choice
typesafe
qwen3.5
Eval Results (legacy)
Instructions to use jaredpalmer/kev-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jaredpalmer/kev-4b with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3.5-4B-Base") model = PeftModel.from_pretrained(base_model, "jaredpalmer/kev-4b") - Notebooks
- Google Colab
- Kaggle
Download head.pt from jaredpalmer/kev-4b: direct link, hf CLI and curl.
- Browser
- Download file 5.25 MB
-
https://huggingface.co/jaredpalmer/kev-4b/resolve/main/head.pt
- Command line
-
hf download hf://jaredpalmer/kev-4b/head.pt
-
curl -L -o head.pt https://huggingface.co/jaredpalmer/kev-4b/resolve/main/head.pt
5.25 MB
- Xet hash:
- fdfd452dbf570f8d39bf40c5bc23c6480571f5bc359766fec65a67c5bfcdc320
- Size of remote file:
- 5.25 MB
- SHA256:
- dd633435998ecc751ac538717a3742e32149500fabf7d7276287dbf0693f347c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.