Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use jakariamd/opp_115_policy_change with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jakariamd/opp_115_policy_change with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jakariamd/opp_115_policy_change")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jakariamd/opp_115_policy_change") model = AutoModelForSequenceClassification.from_pretrained("jakariamd/opp_115_policy_change", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83ddc7ab4a77b97413ebe3cbde14331ec96f8406e96c24e73a9a4b3f43077c22
- Size of remote file:
- 499 MB
- SHA256:
- f1a3a57ec351af6024349337a9c822d42529447bf8278e66268acaab921e71be
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