Instructions to use alinet/bart-base-balanced-resolved-qg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alinet/bart-base-balanced-resolved-qg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alinet/bart-base-balanced-resolved-qg") model = AutoModelForSeq2SeqLM.from_pretrained("alinet/bart-base-balanced-resolved-qg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update metadata with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -30,6 +30,9 @@ model-index:
|
|
| 30 |
- type: bertscore
|
| 31 |
value: 0.5983651754615461
|
| 32 |
name: BERTScore F1
|
|
|
|
|
|
|
|
|
|
| 33 |
---
|
| 34 |
|
| 35 |
A question generation model trained on `alinet/balanced_qg` dataset (`resolved` subset).
|
|
|
|
| 30 |
- type: bertscore
|
| 31 |
value: 0.5983651754615461
|
| 32 |
name: BERTScore F1
|
| 33 |
+
- type: bertscore
|
| 34 |
+
value: 0.5884801388565024
|
| 35 |
+
name: BERTScore Precision
|
| 36 |
---
|
| 37 |
|
| 38 |
A question generation model trained on `alinet/balanced_qg` dataset (`resolved` subset).
|