Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use gossminn/predict-perception-bertino-cause-object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gossminn/predict-perception-bertino-cause-object with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gossminn/predict-perception-bertino-cause-object")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gossminn/predict-perception-bertino-cause-object") model = AutoModelForSequenceClassification.from_pretrained("gossminn/predict-perception-bertino-cause-object", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d514d2fd54c1f1b71f205716489728a98d8215e12d30fad1efa87f6e2ad546a
- Size of remote file:
- 273 MB
- SHA256:
- d3d6e4203af6b79e4e02ba6b0c25f292f419b3798bfc382a18030f79ea74907f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.