Instructions to use apperry-ai/fact_extraction_roberta_fixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apperry-ai/fact_extraction_roberta_fixed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="apperry-ai/fact_extraction_roberta_fixed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("apperry-ai/fact_extraction_roberta_fixed") model = AutoModelForTokenClassification.from_pretrained("apperry-ai/fact_extraction_roberta_fixed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from apperry-ai/fact_extraction_roberta_fixed: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/apperry-ai/fact_extraction_roberta_fixed/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://apperry-ai/fact_extraction_roberta_fixed/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/apperry-ai/fact_extraction_roberta_fixed/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- 12ddbdb67533e6a3394a3de5596357d7b07728780e5e95d9b96b6de831e957bc
- Size of remote file:
- 496 MB
- SHA256:
- 29a390e581db73b410ec0088fb52fc6508e54e13c8bf64ac5252945949823ec5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.