Text Classification
Transformers
TensorBoard
Safetensors
Ukrainian
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use lapa-llm/fineweb-nemotron-edu-score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lapa-llm/fineweb-nemotron-edu-score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lapa-llm/fineweb-nemotron-edu-score")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lapa-llm/fineweb-nemotron-edu-score") model = AutoModelForSequenceClassification.from_pretrained("lapa-llm/fineweb-nemotron-edu-score") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d5cac4d92cea4d46eb35847d7c9df3efc3169fe12c165aa4c25af24943d9ad5
- Size of remote file:
- 1.11 GB
- SHA256:
- 2dcfbfa7478aedae790e3b666284a0c8bccc1d055561b2a0f9e289c3e609705a
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