Instructions to use Parsa/BBB_prediction_classification_SMILES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Parsa/BBB_prediction_classification_SMILES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Parsa/BBB_prediction_classification_SMILES")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Parsa/BBB_prediction_classification_SMILES") model = AutoModelForSequenceClassification.from_pretrained("Parsa/BBB_prediction_classification_SMILES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Parsa/BBB_prediction_classification_SMILES: direct link, hf CLI and curl.
- Browser
- Download file 13.7 MB
-
https://huggingface.co/Parsa/BBB_prediction_classification_SMILES/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Parsa/BBB_prediction_classification_SMILES/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Parsa/BBB_prediction_classification_SMILES/resolve/main/pytorch_model.bin
13.7 MB
- Xet hash:
- f2332b33fa9c4d0143b4a17a27586bc2175d0bf3ad51d3150ae91823cff120f0
- Size of remote file:
- 13.7 MB
- SHA256:
- bfe6f5a8f8bb82aec566fdde10ca27bc960e9d6acd0833da76e025a41191d995
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.