Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use profoz/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use profoz/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="profoz/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("profoz/results") model = AutoModelForSequenceClassification.from_pretrained("profoz/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36244bec5d8b7d169b8fd483bdfcb99f39120c0e69b7e081fd95792f81682996
- Size of remote file:
- 6.95 kB
- SHA256:
- d1c781ce3335dac32dd80e83db6a6ef6b662c86da6b3e8a8d4e7bcaf59acc988
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