Text Classification
Transformers
Safetensors
English
distilbert
requirements-engineering
software-engineering
user-stories
qus
quality-assessment
natural-language-processing
text-embeddings-inference
Instructions to use devleoespinosa/DistilBERT-AUSQ-SL-Atomic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devleoespinosa/DistilBERT-AUSQ-SL-Atomic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devleoespinosa/DistilBERT-AUSQ-SL-Atomic")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devleoespinosa/DistilBERT-AUSQ-SL-Atomic") model = AutoModelForSequenceClassification.from_pretrained("devleoespinosa/DistilBERT-AUSQ-SL-Atomic", device_map="auto") - Notebooks
- Google Colab
- Kaggle