Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-bert-focus-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use responsibility-framing/predict-perception-bert-focus-concept with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="responsibility-framing/predict-perception-bert-focus-concept")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-bert-focus-concept") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-bert-focus-concept") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cab7c967c76da37adb6bc41bbc988e19fe53d03934a35432807b7876c6f94ebf
- Size of remote file:
- 3.12 kB
- SHA256:
- febc5015f8adb7f8da9f8b701a44831582e6f01b45c5d8307a4918aefb32ac58
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