Instructions to use danush99/Model_LightOnOCR-Sin-Handwritten-Text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use danush99/Model_LightOnOCR-Sin-Handwritten-Text with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lightonai/LightOnOCR-2-1B") model = PeftModel.from_pretrained(base_model, "danush99/Model_LightOnOCR-Sin-Handwritten-Text") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from danush99/Model_LightOnOCR-Sin-Handwritten-Text: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/danush99/Model_LightOnOCR-Sin-Handwritten-Text/resolve/main/tokenizer.json
- Command line
-
hf download hf://danush99/Model_LightOnOCR-Sin-Handwritten-Text/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/danush99/Model_LightOnOCR-Sin-Handwritten-Text/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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