Transformers
PyTorch
Safetensors
mt5
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use mukayese/mt5-base-turkish-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mukayese/mt5-base-turkish-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mukayese/mt5-base-turkish-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("mukayese/mt5-base-turkish-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
968bf4f
1
Parent(s): 0d59072
Librarian Bot: Add base_model information to model (#3)
Browse files- Librarian Bot: Add base_model information to model (0c7057474c06c7c2cf1f2388dfc077c2c53052c1)
Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>
README.md
CHANGED
|
@@ -6,20 +6,21 @@ datasets:
|
|
| 6 |
- mlsum
|
| 7 |
metrics:
|
| 8 |
- rouge
|
|
|
|
| 9 |
model-index:
|
| 10 |
- name: mt5-base-turkish-sum
|
| 11 |
results:
|
| 12 |
- task:
|
| 13 |
-
name: Summarization
|
| 14 |
type: summarization
|
|
|
|
| 15 |
dataset:
|
| 16 |
name: mlsum tu
|
| 17 |
type: mlsum
|
| 18 |
args: tu
|
| 19 |
metrics:
|
| 20 |
-
-
|
| 21 |
-
type: rouge
|
| 22 |
value: 47.4222
|
|
|
|
| 23 |
---
|
| 24 |
|
| 25 |
|
|
|
|
| 6 |
- mlsum
|
| 7 |
metrics:
|
| 8 |
- rouge
|
| 9 |
+
base_model: google/mt5-base
|
| 10 |
model-index:
|
| 11 |
- name: mt5-base-turkish-sum
|
| 12 |
results:
|
| 13 |
- task:
|
|
|
|
| 14 |
type: summarization
|
| 15 |
+
name: Summarization
|
| 16 |
dataset:
|
| 17 |
name: mlsum tu
|
| 18 |
type: mlsum
|
| 19 |
args: tu
|
| 20 |
metrics:
|
| 21 |
+
- type: rouge
|
|
|
|
| 22 |
value: 47.4222
|
| 23 |
+
name: Rouge1
|
| 24 |
---
|
| 25 |
|
| 26 |
|