Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use lapa-llm/manipulative-score-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lapa-llm/manipulative-score-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lapa-llm/manipulative-score-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lapa-llm/manipulative-score-model") model = AutoModelForSequenceClassification.from_pretrained("lapa-llm/manipulative-score-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c110876dc705fa2bbba45281eb7d089279b8ffd2c8c4d277af4848b95f82c789
- Size of remote file:
- 5.43 kB
- SHA256:
- 7c17a09cfc56dfa6aa6c79527a7d5483d37b0c61039036a9876a08aa77770dba
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