Instructions to use eyaHarbaoui/markuplmForfinanceArticles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eyaHarbaoui/markuplmForfinanceArticles with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="eyaHarbaoui/markuplmForfinanceArticles")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("eyaHarbaoui/markuplmForfinanceArticles") model = AutoModelForTokenClassification.from_pretrained("eyaHarbaoui/markuplmForfinanceArticles", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eyaHarbaoui/markuplmForfinanceArticles: direct link, hf CLI and curl.
- Browser
- Download file 539 MB
-
https://huggingface.co/eyaHarbaoui/markuplmForfinanceArticles/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eyaHarbaoui/markuplmForfinanceArticles/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eyaHarbaoui/markuplmForfinanceArticles/resolve/main/pytorch_model.bin
539 MB
- Xet hash:
- a54873d8d2fad7eaa621b9bb5d3924527630cc1d02468f9309caf43d6f350d46
- Size of remote file:
- 539 MB
- SHA256:
- b706d05e5c7eba474e3917a08eab7ec0b1487f1751ff65b20c1eadb9798b569d
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