Instructions to use Declan/CNN_model_v8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Declan/CNN_model_v8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Declan/CNN_model_v8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Declan/CNN_model_v8") model = AutoModelForMaskedLM.from_pretrained("Declan/CNN_model_v8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Declan/CNN_model_v8: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Declan/CNN_model_v8/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Declan/CNN_model_v8@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Declan/CNN_model_v8/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 8f802a3d26b59767d4b73761dce87d36fdeca358b6e4dfa1278ed91b627c274e
- Size of remote file:
- 438 MB
- SHA256:
- 148b0983762e5a091b2e28f14a02b1e20ef737c39fa88c8725f85b014a4bc4ed
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