Instructions to use dfafdsaf/deberta_sentiment_5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dfafdsaf/deberta_sentiment_5000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dfafdsaf/deberta_sentiment_5000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dfafdsaf/deberta_sentiment_5000") model = AutoModelForSequenceClassification.from_pretrained("dfafdsaf/deberta_sentiment_5000") - Notebooks
- Google Colab
- Kaggle
Upload DebertaV2ForSequenceClassification
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 567601628
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:caa72240d43c9443e34be0699e45383ef8116983017943a4f1602cb92ef98bd0
|
| 3 |
size 567601628
|