Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use lvwerra/distilbert-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lvwerra/distilbert-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lvwerra/distilbert-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lvwerra/distilbert-imdb") model = AutoModelForSequenceClassification.from_pretrained("lvwerra/distilbert-imdb", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lvwerra/distilbert-imdb: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/lvwerra/distilbert-imdb/resolve/main/training_args.bin
- Command line
-
hf download hf://lvwerra/distilbert-imdb/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lvwerra/distilbert-imdb/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 2c212af734d16bc44d702a10942af3af47c7539122dc60d6db720cb1a1637219
- Size of remote file:
- 2.93 kB
- SHA256:
- a78ec6374b76a0152998650386f046a58e63000b66f7fdfbe249fd32c35b8a7a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.