Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use bweb771/deberta_amazon_reviews_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bweb771/deberta_amazon_reviews_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bweb771/deberta_amazon_reviews_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bweb771/deberta_amazon_reviews_v1") model = AutoModelForSequenceClassification.from_pretrained("bweb771/deberta_amazon_reviews_v1") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:426ce6288094c2733fa61d150226de05d3fac77113c48240a99cdcd5eb502fb1
|
| 3 |
+
size 737732700
|