Instructions to use damgomz/fp_bs8_lr2e4_x4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use damgomz/fp_bs8_lr2e4_x4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="damgomz/fp_bs8_lr2e4_x4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("damgomz/fp_bs8_lr2e4_x4") model = AutoModelForMaskedLM.from_pretrained("damgomz/fp_bs8_lr2e4_x4") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -74,3 +74,4 @@ Epoch | Train Loss | Test Loss
|
|
| 74 |
| 4.0 | 6.965905 | 6.969510 |
|
| 75 |
| 4.5 | 6.957660 | 6.966595 |
|
| 76 |
| 5.0 | 6.968893 | 6.967915 |
|
|
|
|
|
|
| 74 |
| 4.0 | 6.965905 | 6.969510 |
|
| 75 |
| 4.5 | 6.957660 | 6.966595 |
|
| 76 |
| 5.0 | 6.968893 | 6.967915 |
|
| 77 |
+
| 5.5 | 6.962095 | 6.962197 |
|