Instructions to use damgomz/fp_bs8_lr1e4_x2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use damgomz/fp_bs8_lr1e4_x2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="damgomz/fp_bs8_lr1e4_x2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("damgomz/fp_bs8_lr1e4_x2") model = AutoModelForMaskedLM.from_pretrained("damgomz/fp_bs8_lr1e4_x2") - 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 | 6.976612 | 6.973448 |
|
| 75 |
| 4.5 | 6.968990 | 6.975167 |
|
| 76 |
| 5.0 | 6.969795 | 6.971316 |
|
|
|
|
|
|
| 74 |
| 4.0 | 6.976612 | 6.973448 |
|
| 75 |
| 4.5 | 6.968990 | 6.975167 |
|
| 76 |
| 5.0 | 6.969795 | 6.971316 |
|
| 77 |
+
| 5.5 | 6.970071 | 6.966503 |
|