Instructions to use sgugger/test-upload1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/test-upload1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/test-upload1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/test-upload1") model = AutoModelForSequenceClassification.from_pretrained("sgugger/test-upload1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d464b40c03a8e143f16ec4e038cc4a0a409ec7a3776bb41dd9ecb981db70915c
- Size of remote file:
- 263 MB
- SHA256:
- fa03bdf6c7f06cac90e08cc4dcc95b97624337889487f8e57732de7b53d05b12
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