Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use tingchih/1025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tingchih/1025 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tingchih/1025")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tingchih/1025") model = AutoModelForSequenceClassification.from_pretrained("tingchih/1025") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Oct26_00-27-54_vision1.cs.vt.edu
- Oct26_00-29-59_vision1.cs.vt.edu
- Oct26_00-32-18_vision1.cs.vt.edu
- Oct26_00-34-11_vision1.cs.vt.edu
- Oct26_00-35-09_vision1.cs.vt.edu
- Oct26_00-36-46_vision1.cs.vt.edu
- Oct26_00-39-01_vision1.cs.vt.edu
- Oct26_00-40-28_vision1.cs.vt.edu
- Oct26_00-43-40_vision1.cs.vt.edu
- Oct26_00-46-33_vision1.cs.vt.edu
- Oct26_00-48-13_vision1.cs.vt.edu