Instructions to use musabg/mt5-large-tr-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use musabg/mt5-large-tr-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("musabg/mt5-large-tr-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("musabg/mt5-large-tr-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:db62767d399a4d7836d69b91f4582551b7097e9adad2f26350a97ee5eede5516
|
| 3 |
+
size 4918393736
|