Feature Extraction
Transformers
Safetensors
bert
chemistry
cheminformatics
materials-science
astra
property-prediction
regression
active-learning
Instructions to use wkdghdus23/astra-predictor-final-eb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wkdghdus23/astra-predictor-final-eb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wkdghdus23/astra-predictor-final-eb")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("wkdghdus23/astra-predictor-final-eb") model = AutoModel.from_pretrained("wkdghdus23/astra-predictor-final-eb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8155f9c6f9a178397454682332404c60be0e4f2a2b67b4c03d9dbd2da5a295d8
- Size of remote file:
- 354 MB
- SHA256:
- 30f3a870e29894440fc2fbbdb73d97ccc90af5a8befa80c3cd38fa37ab0ff370
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