Instructions to use akshat3492/mT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akshat3492/mT5 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="akshat3492/mT5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("akshat3492/mT5") model = AutoModelForSeq2SeqLM.from_pretrained("akshat3492/mT5") - Notebooks
- Google Colab
- Kaggle
Commit ·
a09c26b
1
Parent(s): c3c7f32
Training in progress, step 500
Browse files- pytorch_model.bin +1 -1
- tokenizer.json +1 -1
- training_args.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1200769925
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:03880d424a33a580700560499844b1e9d902f3ddd0cc1ef1c68e18060902a8da
|
| 3 |
size 1200769925
|
tokenizer.json
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 16330466
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:da4980af4e0649bb07a8cffdad7344bba0401a39dc67fb0256b4da603aae65b9
|
| 3 |
size 16330466
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4155
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:231a04409ab29baaac347642748e9cfe8bb28aa7f27ca53a0d4b368229f35aa4
|
| 3 |
size 4155
|