Instructions to use intanm/mbert-webis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intanm/mbert-webis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="intanm/mbert-webis")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("intanm/mbert-webis") model = AutoModelForQuestionAnswering.from_pretrained("intanm/mbert-webis") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2000
Browse files- pytorch_model.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 709125734
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e22a230995ae7f035bab0f5d0d074b5156db3dd01eb0263a9a87c2c4cec4cedd
|
| 3 |
size 709125734
|