Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use NikhilAnil11/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NikhilAnil11/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NikhilAnil11/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NikhilAnil11/results") model = AutoModelForSequenceClassification.from_pretrained("NikhilAnil11/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9641731fa7ea3fc9187fa0f24a8cb1c5568a746bf1ae72f5e961b48633590ae
- Size of remote file:
- 5.3 kB
- SHA256:
- dfe834946339411f033745f84d962e333b804f78929ed8cb87a002b068d40437
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