Instructions to use stevemobs/deberta-base-newsqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stevemobs/deberta-base-newsqa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" 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("question-answering", model="stevemobs/deberta-base-newsqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("stevemobs/deberta-base-newsqa") model = AutoModelForQuestionAnswering.from_pretrained("stevemobs/deberta-base-newsqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 8000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 554483891
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9c1f6ea423933363a494646be6e2745a5e9a79091f075da6233b0d5a2d245f3f
|
| 3 |
size 554483891
|
runs/May29_01-26-49_eb85d1c6a05d/events.out.tfevents.1653787644.eb85d1c6a05d.81.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fe03ff7e107dea3f7128e25db0e69b1f7d1c07028fb69f33f38700563320b388
|
| 3 |
+
size 5924
|