Instructions to use ashwani-tanwar/Gujarati-XLM-R-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashwani-tanwar/Gujarati-XLM-R-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ashwani-tanwar/Gujarati-XLM-R-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ashwani-tanwar/Gujarati-XLM-R-Base") model = AutoModelForMaskedLM.from_pretrained("ashwani-tanwar/Gujarati-XLM-R-Base", 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 sha256:647ef57705f4c4c3bb0f2dfea77e4472871c86a4035a878a2e7e41314535cd59
|
| 3 |
+
size 1116592650
|