Instructions to use thugCodeNinja/robertatemp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thugCodeNinja/robertatemp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thugCodeNinja/robertatemp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thugCodeNinja/robertatemp") model = AutoModelForSequenceClassification.from_pretrained("thugCodeNinja/robertatemp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16b3fb31219cc72799b8c3634c9af4ef815dc926bb941760df30c99418af1357
- Size of remote file:
- 499 MB
- SHA256:
- a8996760c8f36ccc536f7771bc6ad1c9de798664bf7a425114302919f296a3f0
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