Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use leobg/deeva-modcat-seqclass-deberta-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leobg/deeva-modcat-seqclass-deberta-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leobg/deeva-modcat-seqclass-deberta-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leobg/deeva-modcat-seqclass-deberta-v1") model = AutoModelForSequenceClassification.from_pretrained("leobg/deeva-modcat-seqclass-deberta-v1") - 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 sha256:887767894797f6bb51d084d2c9d7f42274c6b4d10fea15fc32da46aae29a6f2a
|
| 3 |
+
size 567632396
|