Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use wdmuer/test-decide-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wdmuer/test-decide-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wdmuer/test-decide-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wdmuer/test-decide-classifier") model = AutoModelForSequenceClassification.from_pretrained("wdmuer/test-decide-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 021b556d66c476610916f75b92d5c1ae05b85681c1874f5c9f2cb9acf1826796
- Size of remote file:
- 5.84 kB
- SHA256:
- 2cf184e7abd7cff45d6f2a61147a69d581b2398a9ac1d5c43dc8c8fbbe68072c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.