Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use hanyp/saved_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hanyp/saved_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hanyp/saved_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hanyp/saved_model") model = AutoModelForSequenceClassification.from_pretrained("hanyp/saved_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f8dd30c33c02b22323bdf54ef1962bdac66295a58ace56821896aaf5a918ef0
- Size of remote file:
- 5.11 kB
- SHA256:
- ed79e4fdd694746972bf002368e41c3a780b0b3f4fbe707a723d7d39c10277af
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