Instructions to use RidzIn/Roberta_FakeNewsDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RidzIn/Roberta_FakeNewsDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RidzIn/Roberta_FakeNewsDetection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RidzIn/Roberta_FakeNewsDetection") model = AutoModelForSequenceClassification.from_pretrained("RidzIn/Roberta_FakeNewsDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload RobertaForSequenceClassification
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 498612824
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f8d7b3b430e961863e6f8a4788faa8feb1557420e4e51f9dde5e13220543d1c4
|
| 3 |
size 498612824
|