[!NOTE] This model uses a custom classification head (mean pooling over a backbone without a native sequence-classification class), so loading requires trust_remote_code=True. vLLM serving requires a standard architecture.

Evaluation

Metric	Value
accuracy	0.7575
f1_macro	0.7568

Usage

python

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("davanstrien/lfm25-encoder-agnews-smoke", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("davanstrien/lfm25-encoder-agnews-smoke", trust_remote_code=True)

inputs = tokenizer("your text here", return_tensors="pt", truncation=True)
print(model.config.id2label[model(**inputs).logits.argmax().item()])

Reproduction

Produced on Hugging Face Jobs (gpu) with the train-classifier.py recipe from uv-scripts. Run it yourself:

bash

hf jobs uv run --flavor gpu --secrets HF_TOKEN \
    https://huggingface.co/datasets/uv-scripts/classification/raw/main/train-classifier.py \
    fancyzhx/ag_news davanstrien/lfm25-encoder-agnews-smoke