Text Classification
Transformers
TensorBoard
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
Instructions to use wbigger/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wbigger/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wbigger/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wbigger/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("wbigger/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7d9697844fdc72706d4e4e79875784ab64bcb86445598953a3c6f119e8b53ca
- Size of remote file:
- 5.3 kB
- SHA256:
- 6d4e8b337ed59303e792c5c244edeb33b2bfe31f1fa5f3eef2f290a85e9c8b28
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