Text Classification
Transformers
Safetensors
English
distilbert
sentiment-analysis
sequence-classification
academic-peer-review
openreview
text-embeddings-inference
Instructions to use EvilScript/academic-sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EvilScript/academic-sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EvilScript/academic-sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EvilScript/academic-sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("EvilScript/academic-sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64cf22c27201fc4edaf39cc01cbe19f6188902323c4b6e19d946610dc3615232
- Size of remote file:
- 268 MB
- SHA256:
- 38c9adf16f21badfe6569b17c551a5167f4deea78f91887519513153a4382eb9
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