Instructions to use mtolgakbaba/mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtolgakbaba/mt5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mtolgakbaba/mt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("mtolgakbaba/mt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
0b7b1be
1
Parent(s): 541a28f
Training in progress, step 500
Browse files
runs/Dec02_14-29-46_17f8b77463ab/events.out.tfevents.1701527814.17f8b77463ab.214.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:edfd882a0cf7cc5898691a886ee5f6e8997a765fa25327b3bb421ec60e859a35
|
| 3 |
+
size 4773
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4792
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:69066d207d86368481f1299c1aff33a9885e94e66ae4704a5299513b9db74a9f
|
| 3 |
size 4792
|