Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Etelis/IMDB_DistilBERT_5EEE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/IMDB_DistilBERT_5EEE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/IMDB_DistilBERT_5EEE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/IMDB_DistilBERT_5EEE") model = AutoModelForSequenceClassification.from_pretrained("Etelis/IMDB_DistilBERT_5EEE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Etelis/IMDB_DistilBERT_5EEE: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/Etelis/IMDB_DistilBERT_5EEE/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://Etelis/IMDB_DistilBERT_5EEE@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Etelis/IMDB_DistilBERT_5EEE/resolve/refs%2Fpr%2F1/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.