Instructions to use Declan/WallStreetJournal_model_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Declan/WallStreetJournal_model_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Declan/WallStreetJournal_model_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Declan/WallStreetJournal_model_v2") model = AutoModelForMaskedLM.from_pretrained("Declan/WallStreetJournal_model_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Declan/WallStreetJournal_model_v2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Declan/WallStreetJournal_model_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Declan/WallStreetJournal_model_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Declan/WallStreetJournal_model_v2/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 9dfe0c34868a4c68730b3a30ab4953b24542624dde10958845f7ee4e671d82d8
- Size of remote file:
- 438 MB
- SHA256:
- a6d0c4c3134b5e90cc20d3163160590bf132fcf4e703f56bb3b95dc8d11501bd
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