Instructions to use textattack/distilbert-base-cased-CoLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/distilbert-base-cased-CoLA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/distilbert-base-cased-CoLA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/distilbert-base-cased-CoLA") model = AutoModelForSequenceClassification.from_pretrained("textattack/distilbert-base-cased-CoLA") - Notebooks
- Google Colab
- Kaggle
Update eval_results_cola.txt
Browse files- eval_results_cola.txt +3 -0
eval_results_cola.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
eval_loss = 0.5608741616209348
|
| 2 |
+
eval_mcc = 0.46372927911071965
|
| 3 |
+
epoch = 3.0
|