Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use tingchih/1025_weight_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tingchih/1025_weight_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tingchih/1025_weight_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tingchih/1025_weight_3") model = AutoModelForSequenceClassification.from_pretrained("tingchih/1025_weight_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e444fb7cea2069fb360dbe2cb8d80240bb807928a9b3ce2813cc4ce1c05d6145
- Size of remote file:
- 438 MB
- SHA256:
- 2150ee1caac3cef719616ebd760ee35f8e599005f6a1720cbfbe6f699621967b
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