Text Classification
PEFT
Safetensors
English
decision-model
calibration
lora
multiple-choice
typesafe
Eval Results (legacy)
Instructions to use jaredpalmer/kev-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jaredpalmer/kev-8b with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3-8B-Base") model = PeftModel.from_pretrained(base_model, "jaredpalmer/kev-8b") - Notebooks
- Google Colab
- Kaggle
Research preview: Qwen3-8B-Base + LoRA r16, decision-v6, lr 5e-5 (trial recipe-8b-r1/00-trial-0); dev 0.869, transfer 0.774; locked test 0.869 / 0.799 (one ungated read)
6466fbd verified Download tokenizer.json from jaredpalmer/kev-8b: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/jaredpalmer/kev-8b/resolve/49352ab2f76914223146ec6a02c7395a9a3d5030/tokenizer.json
- Command line
-
hf download hf://jaredpalmer/kev-8b@49352ab2f76914223146ec6a02c7395a9a3d5030/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/jaredpalmer/kev-8b/resolve/49352ab2f76914223146ec6a02c7395a9a3d5030/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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