Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Toprak1yu/distilbert-imdb-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Toprak1yu/distilbert-imdb-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Toprak1yu/distilbert-imdb-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Toprak1yu/distilbert-imdb-classification") model = AutoModelForSequenceClassification.from_pretrained("Toprak1yu/distilbert-imdb-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Toprak1yu/distilbert-imdb-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.14 kB
-
https://huggingface.co/Toprak1yu/distilbert-imdb-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Toprak1yu/distilbert-imdb-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Toprak1yu/distilbert-imdb-classification/resolve/main/training_args.bin
5.14 kB
- Xet hash:
- 837d4521e00d6f7a943424bf3aafa1f861febb201fc51b78d30209788d5ef6af
- Size of remote file:
- 5.14 kB
- SHA256:
- b23c68c1e9d2251950d48765fcaa743809bc3258dfdde9d6bc6efefc47689051
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.