Instructions to use pnichite/QAClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pnichite/QAClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pnichite/QAClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pnichite/QAClassification") model = AutoModelForSequenceClassification.from_pretrained("pnichite/QAClassification") - Notebooks
- Google Colab
- Kaggle
add model
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 438006125
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:06137ae34b21978c06b922fe9d22b9be21225e923d4ee484627a2afed8af28e9
|
| 3 |
size 438006125
|