Instructions to use srcocotero/tiny-bert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/tiny-bert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/tiny-bert-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/tiny-bert-qa") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/tiny-bert-qa") - Notebooks
- Google Colab
- Kaggle
Commit 路
fd0ca82
1
Parent(s): fdb8461
Upload train_results.json
Browse files- train_results.json +8 -0
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 3.0,
|
| 3 |
+
"train_loss": 2.87008975942873,
|
| 4 |
+
"train_runtime": 858.012,
|
| 5 |
+
"train_samples": 87714,
|
| 6 |
+
"train_samples_per_second": 306.688,
|
| 7 |
+
"train_steps_per_second": 61.338
|
| 8 |
+
}
|