Instructions to use Declan/WallStreetJournal_model_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Declan/WallStreetJournal_model_v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Declan/WallStreetJournal_model_v4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Declan/WallStreetJournal_model_v4") model = AutoModelForMaskedLM.from_pretrained("Declan/WallStreetJournal_model_v4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Declan/WallStreetJournal_model_v4: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Declan/WallStreetJournal_model_v4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Declan/WallStreetJournal_model_v4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Declan/WallStreetJournal_model_v4/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 191c59de98a8703a2cf6a1bab4872055966e651835a44354fc1dfccd71d934c1
- Size of remote file:
- 438 MB
- SHA256:
- 25b3409dad8cee3713ba0c5b92bfe7f435b05686a1b3d074df7a2cd46b004d91
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