Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use piotrtrochim/action_from_text_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use piotrtrochim/action_from_text_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="piotrtrochim/action_from_text_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("piotrtrochim/action_from_text_model") model = AutoModelForSequenceClassification.from_pretrained("piotrtrochim/action_from_text_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f206f51d379a5501d73b7a432f92c754f3066008aa2316c266c25881d26d4e2d
- Size of remote file:
- 3.96 kB
- SHA256:
- 5288875a80b0f2814104da0ebd47ef66d46c75ff4d0432aa833629f597e44049
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