Instructions to use igor-im/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use igor-im/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="igor-im/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("igor-im/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("igor-im/test_trainer") - Notebooks
- Google Colab
- Kaggle
igor commited on
Update README.md
Browse files
README.md
CHANGED
|
@@ -23,7 +23,8 @@ It achieves the following results on the evaluation set:
|
|
| 23 |
|
| 24 |
## Model description
|
| 25 |
|
| 26 |
-
|
|
|
|
| 27 |
|
| 28 |
## Intended uses & limitations
|
| 29 |
|
|
|
|
| 23 |
|
| 24 |
## Model description
|
| 25 |
|
| 26 |
+
WIP
|
| 27 |
+
Currently seems to be pretty bad overfit. I have an idea where, data distribution is kind of off (need to drop unknown classifications), so next version will hopefully be better
|
| 28 |
|
| 29 |
## Intended uses & limitations
|
| 30 |
|