Text Classification
Transformers
PyTorch
TensorFlow
JAX
English
roberta
sentiment
twitter
reviews
siebert
Instructions to use siebert/sentiment-roberta-large-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use siebert/sentiment-roberta-large-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="siebert/sentiment-roberta-large-english")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("siebert/sentiment-roberta-large-english") model = AutoModelForSequenceClassification.from_pretrained("siebert/sentiment-roberta-large-english") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4709e8601d35e5e3dfb9b5f85d0f0342058b42eff37d636ab4ac491cf64fc558
- Size of remote file:
- 1.42 GB
- SHA256:
- 805688de73481b1175b1e06f05a971144dceb7e0064b64a84b78a3685eb3209d
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