Text Classification
Transformers
PyTorch
Turkish
deberta-v2
subjectivity
CLEF2023
text-embeddings-inference
Instructions to use GroNLP/mdebertav3-subjectivity-turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/mdebertav3-subjectivity-turkish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GroNLP/mdebertav3-subjectivity-turkish")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GroNLP/mdebertav3-subjectivity-turkish") model = AutoModelForSequenceClassification.from_pretrained("GroNLP/mdebertav3-subjectivity-turkish") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d117f4ef8fcae5f2fda43677f584c78788acd2a7f37cc8a6b8b0c6e28b5ec654
|
| 3 |
+
size 1112513736
|