Instructions to use JFoz/esm2_t12_35M_UR50D-finetuned-localization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JFoz/esm2_t12_35M_UR50D-finetuned-localization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JFoz/esm2_t12_35M_UR50D-finetuned-localization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JFoz/esm2_t12_35M_UR50D-finetuned-localization") model = AutoModelForSequenceClassification.from_pretrained("JFoz/esm2_t12_35M_UR50D-finetuned-localization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e648cb03304ab0f8c54162cdd545c99ef497b8544e81887796d701ee08f1fae
- Size of remote file:
- 4.66 kB
- SHA256:
- 05507a0927a1b665ac51de0158bcd18ec8a0f2d2812bdddcd6051676002a5103
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