Instructions to use oya163/NepBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oya163/NepBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="oya163/NepBERT", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("oya163/NepBERT") model = AutoModel.from_pretrained("oya163/NepBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:82c64afa38c3cb5e7c32b260619f441d810a72b4037c9f23d4d49eb7b529f8e5
|
| 3 |
+
size 333825330
|