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:
- 35c273b9aa5be466fd3fa206395de486f5ee53ad4abb6b317daab8e1f34f0a17
- Size of remote file:
- 7 kB
- SHA256:
- 3ef7f22abe8e1a98e0b4ddd5775a34d01309a42b86b8e2cb0de211a9fa2f6a6b
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