Instructions to use evjohnson/ADR_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use evjohnson/ADR_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="evjohnson/ADR_Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("evjohnson/ADR_Model") model = AutoModelForSequenceClassification.from_pretrained("evjohnson/ADR_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from evjohnson/ADR_Model: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/evjohnson/ADR_Model/resolve/main/model.safetensors
- Command line
-
hf download hf://evjohnson/ADR_Model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/evjohnson/ADR_Model/resolve/main/model.safetensors
738 MB
- Xet hash:
- 2a3b2d054703daef342390801d07bdbad6062c19dd93d7fe2b9a04d41614a745
- Size of remote file:
- 738 MB
- SHA256:
- 3abb98737335f5f06164fb251f53e867a8f1b0298b44dd40a3f235818c1a4ea8
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