Instructions to use mrm8488/bert-tiny-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-tiny-finetuned-squadv2 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="mrm8488/bert-tiny-finetuned-squadv2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-tiny-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/bert-tiny-finetuned-squadv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit 路
3116fd1
1
Parent(s): 975a82f
allow flax
Browse files- .gitattributes +1 -0
.gitattributes
CHANGED
|
@@ -6,3 +6,4 @@
|
|
| 6 |
*.tar.gz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 8 |
*.onnx filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 6 |
*.tar.gz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 8 |
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 9 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|