Text Classification
Transformers
Safetensors
Turkish
bert
ABSA
Sentiment
Transformer
BERT
Turkish
text-embeddings-inference
Instructions to use ebrukilic/bert-absa-tr-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ebrukilic/bert-absa-tr-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ebrukilic/bert-absa-tr-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ebrukilic/bert-absa-tr-v3") model = AutoModelForSequenceClassification.from_pretrained("ebrukilic/bert-absa-tr-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -43,7 +43,7 @@ model = AutoModelForSequenceClassification.from_pretrained("ebrukilic/tubitak_cl
|
|
| 43 |
|
| 44 |
Model tipi: Transformer (BERT tabanlı)
|
| 45 |
|
| 46 |
-
Eğitim veri kümesi:
|
| 47 |
|
| 48 |
Etiketler: ["negatif", "nötr", "pozitif"]
|
| 49 |
|
|
|
|
| 43 |
|
| 44 |
Model tipi: Transformer (BERT tabanlı)
|
| 45 |
|
| 46 |
+
Eğitim veri kümesi: ebrukilic/tubitak_clothing_absa_v3 (8396 eğitim verisi + 4011 test verisi)
|
| 47 |
|
| 48 |
Etiketler: ["negatif", "nötr", "pozitif"]
|
| 49 |
|