Instructions to use Declan/HuffPost_model_v8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Declan/HuffPost_model_v8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Declan/HuffPost_model_v8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Declan/HuffPost_model_v8") model = AutoModelForMaskedLM.from_pretrained("Declan/HuffPost_model_v8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Declan/HuffPost_model_v8: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Declan/HuffPost_model_v8/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Declan/HuffPost_model_v8@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Declan/HuffPost_model_v8/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 4e69c89790a9d2fbafa3bc20c9476981d8d18d88dd9cd871fe003e5481bff0ed
- Size of remote file:
- 438 MB
- SHA256:
- 39805c01d0ed2c66052dfbafb5d922ddfe01f98d37fe3878141ca307bcae2129
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.