Instructions to use whitedevil0089devil/roberta_base_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whitedevil0089devil/roberta_base_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whitedevil0089devil/roberta_base_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whitedevil0089devil/roberta_base_1") model = AutoModelForSequenceClassification.from_pretrained("whitedevil0089devil/roberta_base_1") - Notebooks
- Google Colab
- Kaggle
Upload training_data.json
Browse files- .gitattributes +1 -0
- training_data.json +3 -0
.gitattributes
CHANGED
|
@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
class_info.json filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
class_info.json filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
training_data.json filter=lfs diff=lfs merge=lfs -text
|
training_data.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7fb100504008f6e8e57d971e2a7e46cc894c4f9dd94051331c0fdd8a1824a4a0
|
| 3 |
+
size 143832158
|