Instructions to use SRDdev/MaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/MaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SRDdev/MaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SRDdev/MaskedLM") model = AutoModelForMaskedLM.from_pretrained("SRDdev/MaskedLM") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -26,11 +26,18 @@ Hinglish-Top [Dataset](https://huggingface.co/datasets/WillHeld/hinglish_top) co
|
|
| 26 |
- domain
|
| 27 |
|
| 28 |
### Training
|
| 29 |
-
|
|
| 30 |
-
|:--
|
| 31 |
-
|
|
| 32 |
-
|
| 33 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 34 |
|
| 35 |
### Inference
|
| 36 |
```python
|
|
|
|
| 26 |
- domain
|
| 27 |
|
| 28 |
### Training
|
| 29 |
+
|Epoch|Loss|
|
| 30 |
+
|:--:|:--:|
|
| 31 |
+
|1 |0.0485|
|
| 32 |
+
|2 |0.00837|
|
| 33 |
+
|3 |0.00812|
|
| 34 |
+
|4 |0.0029|
|
| 35 |
+
|5 |0.014|
|
| 36 |
+
|6 |0.00748|
|
| 37 |
+
|7 |0.0041|
|
| 38 |
+
|8 |0.00543|
|
| 39 |
+
|9 |0.00304|
|
| 40 |
+
|10 |0.000574|
|
| 41 |
|
| 42 |
### Inference
|
| 43 |
```python
|