Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
sentiment-analysis
text-embeddings-inference
Instructions to use DerivedFunction01/roberta-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DerivedFunction01/roberta-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DerivedFunction01/roberta-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DerivedFunction01/roberta-imdb") model = AutoModelForSequenceClassification.from_pretrained("DerivedFunction01/roberta-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from DerivedFunction01/roberta-imdb: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/DerivedFunction01/roberta-imdb/resolve/main/training_args.bin
- Command line
-
hf download hf://DerivedFunction01/roberta-imdb/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/DerivedFunction01/roberta-imdb/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 4d0bdc711e56663f2774f93216e1dbf37a08e6d78311914169445e8a3caea032
- Size of remote file:
- 5.2 kB
- SHA256:
- 1a9dc302a36a7af4feda95ea82d8fbf031597604cb2c915690220bc3098f0780
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