Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use candylion/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use candylion/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="candylion/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("candylion/model_output") model = AutoModelForSequenceClassification.from_pretrained("candylion/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0b7bb9b3fd36ecb52b70282e5df3e2329891acd693d6404ba6ae5d83990fc4e
- Size of remote file:
- 5.18 kB
- SHA256:
- 245ae9b733f30233af87e774bd324faf21c1d787a2876a1ab49a7f5192a7b044
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