Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3
deberta-v2`
deberta-mnli
Instructions to use NDugar/2epochv3mlni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NDugar/2epochv3mlni with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NDugar/2epochv3mlni")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NDugar/2epochv3mlni") model = AutoModelForSequenceClassification.from_pretrained("NDugar/2epochv3mlni") - Notebooks
- Google Colab
- Kaggle
Upload scheduler.pt with git-lfs
Browse files- scheduler.pt +3 -0
scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c5b32ff9a5633f382e5393e1f00972fd3e41e887241bf4ed74198b52d98f4a45
|
| 3 |
+
size 623
|