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
Update README.md
Browse files
README.md
CHANGED
|
@@ -16,7 +16,7 @@ model-index:
|
|
| 16 |
# Python-Edu Scorer
|
| 17 |
|
| 18 |
This model is a fine-tuned version of [Snowflake/snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m) on a dataset of Python files labeled by Llama3 for educational value.
|
| 19 |
-
We used this classifier to build the [Python-Edu](https://huggingface.co/datasets/HuggingFaceTB/
|
| 20 |
|
| 21 |
### How to use in transformers
|
| 22 |
To load the Python-Edu classifier, use the following code:
|
|
|
|
| 16 |
# Python-Edu Scorer
|
| 17 |
|
| 18 |
This model is a fine-tuned version of [Snowflake/snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m) on a dataset of Python files labeled by Llama3 for educational value.
|
| 19 |
+
We used this classifier to build the [Python-Edu](https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus) dataset.
|
| 20 |
|
| 21 |
### How to use in transformers
|
| 22 |
To load the Python-Edu classifier, use the following code:
|