Instructions to use rach405/test_trainer6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rach405/test_trainer6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rach405/test_trainer6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rach405/test_trainer6") model = AutoModelForSequenceClassification.from_pretrained("rach405/test_trainer6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf7a56bf0e8748ad5ef97d0e4ccfd2c55153874ada635aa763b2ad67af6e63be
- Size of remote file:
- 2.99 kB
- SHA256:
- bca382b7fbd93674e2fe81adbc909aafcddcefc1f279e797fb1a121d27798e75
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