Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ndiy/ASAP_SENT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ndiy/ASAP_SENT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ndiy/ASAP_SENT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ndiy/ASAP_SENT") model = AutoModelForSequenceClassification.from_pretrained("ndiy/ASAP_SENT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e606452c45083c84f34ab9eb01af2ba95ef1a8d69124c4d04855c3444a43694
- Size of remote file:
- 4.92 kB
- SHA256:
- 77fc753cb9b48da4e0084269a7135ed18aeb6618097cf82ffec182b073931c20
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