Instructions to use Mathnub/imdb-score-predict-roberta-large-fulldata with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathnub/imdb-score-predict-roberta-large-fulldata with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mathnub/imdb-score-predict-roberta-large-fulldata")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mathnub/imdb-score-predict-roberta-large-fulldata") model = AutoModelForSequenceClassification.from_pretrained("Mathnub/imdb-score-predict-roberta-large-fulldata", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mathnub/imdb-score-predict-roberta-large-fulldata: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Mathnub/imdb-score-predict-roberta-large-fulldata/resolve/main/training_args.bin
- Command line
-
hf download hf://Mathnub/imdb-score-predict-roberta-large-fulldata/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mathnub/imdb-score-predict-roberta-large-fulldata/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 81942cbff7e54708846a772efe040d65e1de895f5883cb31e001b1d46dcac30b
- Size of remote file:
- 3.96 kB
- SHA256:
- f4116e94e7a7bd1745dbebdee381d8f1d50861f74292cfddbb229d615581c6b6
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