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
running kev on dgx-spark
#2 opened 5 days ago
by
pawlz