Text Classification
Transformers
Safetensors
English
qwen3_5_text
feature-extraction
decision-model
calibration
full-weight-sft
weight-averaging
multiple-choice
typesafe
qwen3.8
Eval Results (legacy)
Instructions to use jaredpalmer/kev-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaredpalmer/kev-27b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jaredpalmer/kev-27b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jaredpalmer/kev-27b") model = AutoModel.from_pretrained("jaredpalmer/kev-27b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Please don’t overwrite existing models
#1
by EwoutH - opened
Please just release a new repo with the new model. Overwriting existing models breaks workflows (unexpectedly!) and is not good for transparency.
Noted for the future. Thanks for feedback
jaredpalmer changed discussion status to closed