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
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()])
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
Runs of davanstrien lfm25-encoder-agnews-smoke on huggingface.co
16
Total runs
1
24-hour runs
2
3-day runs
4
7-day runs
7
30-day runs
More Information About lfm25-encoder-agnews-smoke huggingface.co Model
lfm25-encoder-agnews-smoke huggingface.co
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lfm25-encoder-agnews-smoke is an open source model from GitHub that offers a free installation service, and any user can find lfm25-encoder-agnews-smoke on GitHub to install. At the same time, huggingface.co provides the effect of lfm25-encoder-agnews-smoke install, users can directly use lfm25-encoder-agnews-smoke installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
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