Instructions to use Akari/albert-base-v2-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akari/albert-base-v2-finetuned-squad 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="Akari/albert-base-v2-finetuned-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Akari/albert-base-v2-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("Akari/albert-base-v2-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 23500
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 49123599
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e7d045416ef5bf638bdf853b8863edaa4b87543e4d6f2db6420c7ea4aaf190a7
|
| 3 |
size 49123599
|
runs/Dec01_01-04-08_bigtensor/events.out.tfevents.1638338656.bigtensor.4891.0
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:bcfe7f24e7a97a998fb05ba5da8fd238af47e035fe9805fa3e4629e89eee3e2d
|
| 3 |
+
size 11400
|