Instructions to use itskamran/esm2-finetuned-localization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itskamran/esm2-finetuned-localization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="itskamran/esm2-finetuned-localization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("itskamran/esm2-finetuned-localization") model = AutoModelForSequenceClassification.from_pretrained("itskamran/esm2-finetuned-localization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93fb6e4ef44b2d22009b411e2f472fff032b53f9312fd3a811a02f0b22b63f25
- Size of remote file:
- 136 MB
- SHA256:
- 3ac40635b5d89d2b2daee90a917234bcd86df509c4edd6a958e5ac4bc66ec488
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.