Instructions to use Jeska/BertjeWDialDataQA20k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeska/BertjeWDialDataQA20k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jeska/BertjeWDialDataQA20k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jeska/BertjeWDialDataQA20k") model = AutoModelForMaskedLM.from_pretrained("Jeska/BertjeWDialDataQA20k") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- pytorch_model.bin +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 436760875
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:471735d6a0c51e80f274d23b5235e043aa5b4aab100cf9d1c055af5753ced9c4
|
| 3 |
size 436760875
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 2863
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2414b9e804022788a3eefef154ac6826581291ffbfa06d2879bbbb0fda1d2ed8
|
| 3 |
size 2863
|