Instructions to use cflyuke/bert-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cflyuke/bert-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cflyuke/bert-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cflyuke/bert-sst2") model = AutoModelForSequenceClassification.from_pretrained("cflyuke/bert-sst2") - Notebooks
- Google Colab
- Kaggle
yukee commited on
Update readme
Browse files
README.md
CHANGED
|
@@ -1,6 +1,13 @@
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
---
|
| 5 |
|
| 6 |
# Model Card for Model ID
|
|
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
+
license: apache-2.0
|
| 4 |
+
datasets:
|
| 5 |
+
- gimmaru/glue-sst2
|
| 6 |
+
metrics:
|
| 7 |
+
- accuracy
|
| 8 |
+
base_model:
|
| 9 |
+
- google-bert/bert-base-uncased
|
| 10 |
+
pipeline_tag: text-classification
|
| 11 |
---
|
| 12 |
|
| 13 |
# Model Card for Model ID
|