Text Classification
Transformers
Safetensors
English
distilbert
text-generation-inference
spam-detection
nlp
binary-classification
text-embeddings-inference
Instructions to use kenbaker-gif/Email_Spam_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kenbaker-gif/Email_Spam_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kenbaker-gif/Email_Spam_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kenbaker-gif/Email_Spam_Classifier") model = AutoModelForSequenceClassification.from_pretrained("kenbaker-gif/Email_Spam_Classifier") - 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 sha256:1f8ea9757385a907e446b7a1470bca799f3f097ea9563895dd31a34b526561d1
|
| 3 |
size 498612824
|