Instructions to use j-hartmann/sentiment-roberta-large-english-3-classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use j-hartmann/sentiment-roberta-large-english-3-classes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="j-hartmann/sentiment-roberta-large-english-3-classes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("j-hartmann/sentiment-roberta-large-english-3-classes") model = AutoModelForSequenceClassification.from_pretrained("j-hartmann/sentiment-roberta-large-english-3-classes") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe9b9706d1ca11c43e5f72473adbd0934d75a8dba7894bc3fed9b15883c2077d
- Size of remote file:
- 1.43 GB
- SHA256:
- 13b57175f0f1304d24b96556c9120df1a42294f40ec2b306c58d0c7f8f5d6614
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