Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use C-Stuti/temp_model_outputdir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use C-Stuti/temp_model_outputdir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="C-Stuti/temp_model_outputdir")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("C-Stuti/temp_model_outputdir") model = AutoModelForSequenceClassification.from_pretrained("C-Stuti/temp_model_outputdir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19f852512c5c831c7d40d6fb2bfabf38d98a1870a3645ee374d43e7f069928ba
- Size of remote file:
- 4.35 kB
- SHA256:
- 65f93fe4c03b0563cb5ea918a620cab77002da96c2660bdd892199fe12b7d923
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