Instructions to use mail4dy/fune_tuned_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mail4dy/fune_tuned_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mail4dy/fune_tuned_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mail4dy/fune_tuned_model") model = AutoModelForSequenceClassification.from_pretrained("mail4dy/fune_tuned_model") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForSequenceClassification
Browse files- config.json +0 -1
config.json
CHANGED
|
@@ -14,7 +14,6 @@
|
|
| 14 |
"n_heads": 12,
|
| 15 |
"n_layers": 6,
|
| 16 |
"pad_token_id": 0,
|
| 17 |
-
"problem_type": "single_label_classification",
|
| 18 |
"qa_dropout": 0.1,
|
| 19 |
"seq_classif_dropout": 0.2,
|
| 20 |
"sinusoidal_pos_embds": false,
|
|
|
|
| 14 |
"n_heads": 12,
|
| 15 |
"n_layers": 6,
|
| 16 |
"pad_token_id": 0,
|
|
|
|
| 17 |
"qa_dropout": 0.1,
|
| 18 |
"seq_classif_dropout": 0.2,
|
| 19 |
"sinusoidal_pos_embds": false,
|