Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use at2507/finetuned_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use at2507/finetuned_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="at2507/finetuned_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("at2507/finetuned_model") model = AutoModelForSequenceClassification.from_pretrained("at2507/finetuned_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79b4b307e6cf6335c2a71bb0345fb24e3e213007518030f6099ad80d7d9f835d
- Size of remote file:
- 3.96 kB
- SHA256:
- 5a784d9698437591cc8d47991f670f4a2d956e0c1f0ab70db2cf6c43984e67c1
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