Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/imdb_distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/imdb_distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/imdb_distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/imdb_distilbert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/imdb_distilbert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ab65993aab50c951ce86c8531e5d6938dfba1abe6df670baed0d01506181539
- Size of remote file:
- 4.6 kB
- SHA256:
- 742d75f6c495eebc5bb4c7f02515ffa1019b4e0b310576fae1ec6d38de76261e
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