Instructions to use Declan/WallStreetJournal_model_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Declan/WallStreetJournal_model_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Declan/WallStreetJournal_model_v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Declan/WallStreetJournal_model_v3") model = AutoModelForMaskedLM.from_pretrained("Declan/WallStreetJournal_model_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Declan/WallStreetJournal_model_v3: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Declan/WallStreetJournal_model_v3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Declan/WallStreetJournal_model_v3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Declan/WallStreetJournal_model_v3/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c0d064b05c9335ae7782343c2986e5fac17b5ea189fc830a50bedbfd7694be2f
- Size of remote file:
- 438 MB
- SHA256:
- 1c906663c2593092b9e9ef0e8bee84e1864f44d4476a4440b986cb6da01d0f35
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