Hugging Face's logo

woland2k
/
unspsc-base

Text Classification
Transformers
Safetensors
distilbert
unspsc
text-embeddings-inference
Model card Files
xet
 Community
How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="woland2k/unspsc-base")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("woland2k/unspsc-base")
model = AutoModelForSequenceClassification.from_pretrained("woland2k/unspsc-base")
Quick Links

results

It achieves the following results on the evaluation set:

  • Loss: 1.6502
  • Accuracy: 0.8907

Model description

This model predicts UNSPSC code based on the product name.

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
Downloads last month
10
Safetensors
Model size
70M params
Tensor type
F32
·
Inference Providers NEW
Text Classification
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support