Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-bert-focus-object 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-object 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-object")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-bert-focus-object") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-bert-focus-object", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from responsibility-framing/predict-perception-bert-focus-object: direct link, hf CLI and curl.
- Browser
- Download file 725 kB
-
https://huggingface.co/responsibility-framing/predict-perception-bert-focus-object/resolve/main/tokenizer.json
- Command line
-
hf download hf://responsibility-framing/predict-perception-bert-focus-object/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/responsibility-framing/predict-perception-bert-focus-object/resolve/main/tokenizer.json
725 kB
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