Token Classification
Transformers
Safetensors
English
distilbert
document-understanding
procurement
india
gem
synthetic-data
Instructions to use HarshilDaGoat/gem-certificate-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HarshilDaGoat/gem-certificate-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HarshilDaGoat/gem-certificate-extractor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HarshilDaGoat/gem-certificate-extractor") model = AutoModelForTokenClassification.from_pretrained("HarshilDaGoat/gem-certificate-extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HarshilDaGoat/gem-certificate-extractor: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/HarshilDaGoat/gem-certificate-extractor/resolve/main/training_args.bin
- Command line
-
hf download hf://HarshilDaGoat/gem-certificate-extractor/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HarshilDaGoat/gem-certificate-extractor/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- d10b2c39a8885e0bc86f09c5640530681a413f9f100df8a854e33d80552f7d1c
- Size of remote file:
- 5.27 kB
- SHA256:
- 5f98a77b89a5a75458f58e8ff6427bfd9d7e513bad0562966d01d1f0c5fbe3bd
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