Instructions to use HuggingFaceTB/python-edu-scorer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceTB/python-edu-scorer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceTB/python-edu-scorer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceTB/python-edu-scorer") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceTB/python-edu-scorer") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 23000
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 437955572
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2e32bf0e7b1d47171006df76e1726855c0f982bd9de2c86e34a1a915b0789bb9
|
| 3 |
size 437955572
|