Text Classification
Transformers
PyTorch
bert
Generated from Trainer
sibyl
Eval Results (legacy)
text-embeddings-inference
Instructions to use fabriceyhc/bert-base-uncased-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fabriceyhc/bert-base-uncased-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fabriceyhc/bert-base-uncased-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fabriceyhc/bert-base-uncased-imdb") model = AutoModelForSequenceClassification.from_pretrained("fabriceyhc/bert-base-uncased-imdb") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#5 opened over 1 year ago
by
SFconvertbot
Add evaluation results on the plain_text config and test split of imdb
#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