Instructions to use Lifan-Z/distilbert-base-uncased-finetuned-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lifan-Z/distilbert-base-uncased-finetuned-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Lifan-Z/distilbert-base-uncased-finetuned-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Lifan-Z/distilbert-base-uncased-finetuned-imdb") model = AutoModelForMaskedLM.from_pretrained("Lifan-Z/distilbert-base-uncased-finetuned-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Lifan-Z/distilbert-base-uncased-finetuned-imdb: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Lifan-Z/distilbert-base-uncased-finetuned-imdb/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Lifan-Z/distilbert-base-uncased-finetuned-imdb@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Lifan-Z/distilbert-base-uncased-finetuned-imdb/resolve/refs%2Fpr%2F1/training_args.bin
4.54 kB
- Xet hash:
- c3c27b74e3ff795ec70d26f9cd8419d4fce23d11c5005bda0bb01d3f3c1614fc
- Size of remote file:
- 4.54 kB
- SHA256:
- 5cf55675d7a7ce0b6f1a2d69c3bd97795697057636705b8c49008253fa66d3d6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.