Text Classification
Transformers
Safetensors
English
mpnet
edu score
data filter
text-embeddings-inference
Instructions to use pszemraj/mpnet-base-edu-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pszemraj/mpnet-base-edu-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pszemraj/mpnet-base-edu-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pszemraj/mpnet-base-edu-classifier") model = AutoModelForSequenceClassification.from_pretrained("pszemraj/mpnet-base-edu-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "min_value": 0.0, | |
| "max_value": 5.0, | |
| "metadata": { | |
| "dataset": "HuggingFaceFW/fineweb-edu-llama3-annotations", | |
| "task": "regression", | |
| "num_examples": 444052, | |
| "stats": { | |
| "mean": 1.2964269950366174, | |
| "min": 0.0, | |
| "max": 5.0, | |
| "std_dev": 0.8377157123327311 | |
| } | |
| } | |
| } |