Instructions to use UDHOV/mbert-nepali-hate-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UDHOV/mbert-nepali-hate-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UDHOV/mbert-nepali-hate-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UDHOV/mbert-nepali-hate-classification") model = AutoModelForSequenceClassification.from_pretrained("UDHOV/mbert-nepali-hate-classification") - Notebooks
- Google Colab
- Kaggle
Upload label_encoder.pkl with huggingface_hub
Browse files- label_encoder.pkl +3 -0
label_encoder.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fe80409c375b09d7a584ce0db2991d04bfe1faa5cb3e69f67e04b1c330365a5e
|
| 3 |
+
size 493
|