Instructions to use Declan/Reuters_model_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Declan/Reuters_model_v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Declan/Reuters_model_v4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Declan/Reuters_model_v4") model = AutoModelForMaskedLM.from_pretrained("Declan/Reuters_model_v4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Declan/Reuters_model_v4: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Declan/Reuters_model_v4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Declan/Reuters_model_v4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Declan/Reuters_model_v4/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 96c52ebea55d2bf388a4a106092f550812219d1121a1683d50dbcbbd716734cf
- Size of remote file:
- 438 MB
- SHA256:
- 0b55a9c7271f3669b900dbbab747b09750436984a550431f519eb7b8d096e999
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