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
# 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")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mathnub/imdb-score-predict-roberta-large-fulldata")