Instructions to use Edelweisse/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Edelweisse/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Edelweisse/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Edelweisse/results") model = AutoModelForSequenceClassification.from_pretrained("Edelweisse/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -16,8 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 16 |
|
| 17 |
# results
|
| 18 |
|
| 19 |
-
This model is a fine-tuned
|
| 20 |
-
It achieves the following results on the evaluation set:
|
| 21 |
- Loss: 0.4952
|
| 22 |
- Accuracy: 0.8351
|
| 23 |
- F1: 0.8359
|
|
|
|
| 16 |
|
| 17 |
# results
|
| 18 |
|
| 19 |
+
This model is a fine-tuned results on the evaluation set:
|
|
|
|
| 20 |
- Loss: 0.4952
|
| 21 |
- Accuracy: 0.8351
|
| 22 |
- F1: 0.8359
|