Text Classification
Transformers
PyTorch
English
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use andi611/distilbert-base-uncased-qa-boolq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andi611/distilbert-base-uncased-qa-boolq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="andi611/distilbert-base-uncased-qa-boolq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("andi611/distilbert-base-uncased-qa-boolq") model = AutoModelForSequenceClassification.from_pretrained("andi611/distilbert-base-uncased-qa-boolq") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Update Hugging Face dataset ID
#5 opened about 2 years ago
by
librarian-bot
Add evaluation results on the default config and train split of boolq
#4 opened over 2 years ago
by
autoevaluator
Librarian Bot: Add base_model information to model
#3 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot
Add evaluation results on the default config of boolq
#1 opened over 3 years ago
by
autoevaluator