Instructions to use elftsdmr/5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elftsdmr/5000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="elftsdmr/5000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elftsdmr/5000") model = AutoModelForSequenceClassification.from_pretrained("elftsdmr/5000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b97bf182adab371b9a126ef9882ba61b3701e0ac604549debd8ce0956f1ba049
- Size of remote file:
- 3.58 kB
- SHA256:
- ffcf70531e56e60546b169c9b3509386952072d61756b92217096761d96510b3
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