Instructions to use halilibr/dilbazlar-binary-disorder-detection-model-acc-96 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halilibr/dilbazlar-binary-disorder-detection-model-acc-96 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="halilibr/dilbazlar-binary-disorder-detection-model-acc-96")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("halilibr/dilbazlar-binary-disorder-detection-model-acc-96") model = AutoModelForSequenceClassification.from_pretrained("halilibr/dilbazlar-binary-disorder-detection-model-acc-96", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 737411072
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5fdd1e3be8ce2ff98a3e185e7ce04d49471be33583768221846d393dcee6303b
|
| 3 |
size 737411072
|