Instructions to use Mathnub/imdb-score-predict-distilbert2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathnub/imdb-score-predict-distilbert2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mathnub/imdb-score-predict-distilbert2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mathnub/imdb-score-predict-distilbert2") model = AutoModelForSequenceClassification.from_pretrained("Mathnub/imdb-score-predict-distilbert2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mathnub/imdb-score-predict-distilbert2: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Mathnub/imdb-score-predict-distilbert2/resolve/main/training_args.bin
- Command line
-
hf download hf://Mathnub/imdb-score-predict-distilbert2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mathnub/imdb-score-predict-distilbert2/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 7d2ad814ffde404bffebe293ccb9e434d04c1351a98ee02aff84bb906129e8de
- Size of remote file:
- 3.96 kB
- SHA256:
- d3e8cec2fe625f73fbda3741c8174eeee14c19e18db49ddff24660766e6667fe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.