Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use sgugger/finetuned-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/finetuned-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/finetuned-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/finetuned-bert") model = AutoModelForSequenceClassification.from_pretrained("sgugger/finetuned-bert") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2
by librarian-bot - opened
README.md
CHANGED
|
@@ -21,6 +21,7 @@ model_index:
|
|
| 21 |
name: F1
|
| 22 |
type: f1
|
| 23 |
value: 0.9125214408233276
|
|
|
|
| 24 |
---
|
| 25 |
|
| 26 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
|
| 21 |
name: F1
|
| 22 |
type: f1
|
| 23 |
value: 0.9125214408233276
|
| 24 |
+
base_model: bert-base-cased
|
| 25 |
---
|
| 26 |
|
| 27 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|