Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use yujiepan/bert-base-uncased-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yujiepan/bert-base-uncased-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yujiepan/bert-base-uncased-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yujiepan/bert-base-uncased-imdb") model = AutoModelForSequenceClassification.from_pretrained("yujiepan/bert-base-uncased-imdb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f85d62c02d67726545a911d9cfeb9082dc07958169cf178fc270cebdfe8f5d59
- Size of remote file:
- 3.77 kB
- SHA256:
- 4ffaf73f3c1f4339de1c60e430185af7b3691e0961621089b06a41c7f71c07c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.